Practical Machine Learning For Data Analysis Using Python

Practical Machine Learning For Data Analysis Using Python Book PDF
✏Book Title : Practical Machine Learning for Data Analysis Using Python
✏Author : Abdulhamit Subasi
✏Publisher : Academic Press
✏Release Date : 2020-06-05
✏Pages : 534
✏ISBN : 9780128213803
✏Available Language : English, Spanish, And French

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✏Practical Machine Learning for Data Analysis Using Python Book Summary : Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems. Offers a comprehensive overview of the application of machine learning tools in data analysis across a wide range of subject areas Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data Explores important classification and regression algorithms as well as other machine learning techniques Explains how to use Python to handle data extraction, manipulation, and exploration techniques, as well as how to visualize data spread across multiple dimensions and extract useful features

Practical Machine Learning With Python Book PDF
✏Book Title : Practical Machine Learning with Python
✏Author : Dipanjan Sarkar
✏Publisher : Apress
✏Release Date : 2017-12-20
✏Pages : 530
✏ISBN : 9781484232071
✏Available Language : English, Spanish, And French

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✏Practical Machine Learning with Python Book Summary : Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem. Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today! What You'll Learn Execute end-to-end machine learning projects and systems Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks Review case studies depicting applications of machine learning and deep learning on diverse domains and industries Apply a wide range of machine learning models including regression, classification, and clustering. Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning. Who This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students

📒Practical Machine Learning With R ✍ Brindha Priyadarshini Jeyaraman

Practical Machine Learning With R Book PDF
✏Book Title : Practical Machine Learning with R
✏Author : Brindha Priyadarshini Jeyaraman
✏Publisher : Packt Publishing Ltd
✏Release Date : 2019-08-30
✏Pages : 416
✏ISBN : 9781838552848
✏Available Language : English, Spanish, And French

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✏Practical Machine Learning with R Book Summary : Understand how machine learning works and get hands-on experience of using R to build algorithms that can solve various real-world problems Key Features Gain a comprehensive overview of different machine learning techniques Explore various methods for selecting a particular algorithm Implement a machine learning project from problem definition through to the final model Book Description With huge amounts of data being generated every moment, businesses need applications that apply complex mathematical calculations to data repeatedly and at speed. With machine learning techniques and R, you can easily develop these kinds of applications in an efficient way. Practical Machine Learning with R begins by helping you grasp the basics of machine learning methods, while also highlighting how and why they work. You will understand how to get these algorithms to work in practice, rather than focusing on mathematical derivations. As you progress from one chapter to another, you will gain hands-on experience of building a machine learning solution in R. Next, using R packages such as rpart, random forest, and multiple imputation by chained equations (MICE), you will learn to implement algorithms including neural net classifier, decision trees, and linear and non-linear regression. As you progress through the book, you’ll delve into various machine learning techniques for both supervised and unsupervised learning approaches. In addition to this, you’ll gain insights into partitioning the datasets and mechanisms to evaluate the results from each model and be able to compare them. By the end of this book, you will have gained expertise in solving your business problems, starting by forming a good problem statement, selecting the most appropriate model to solve your problem, and then ensuring that you do not overtrain it. What you will learn Define a problem that can be solved by training a machine learning model Obtain, verify and clean data before transforming it into the correct format for use Perform exploratory analysis and extract features from data Build models for neural net, linear and non-linear regression, classification, and clustering Evaluate the performance of a model with the right metrics Implement a classification problem using the neural net package Employ a decision tree using the random forest library Who this book is for If you are a data analyst, data scientist, or a business analyst who wants to understand the process of machine learning and apply it to a real dataset using R, this book is just what you need. Data scientists who use Python and want to implement their machine learning solutions using R will also find this book very useful. The book will also enable novice programmers to start their journey in data science. Basic knowledge of any programming language is all you need to get started.

Python Machine Learning By Example Book PDF
✏Book Title : Python Machine Learning By Example
✏Author : Yuxi (Hayden) Liu
✏Publisher : Packt Publishing Ltd
✏Release Date : 2020-10-30
✏Pages : 526
✏ISBN : 9781800203860
✏Available Language : English, Spanish, And French

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✏Python Machine Learning By Example Book Summary : Equipped with the latest updates, this third edition of Python Machine Learning By Example provides a comprehensive course for ML enthusiasts to strengthen their command of ML concepts, techniques, and algorithms.

📒Practical Machine Learning ✍ Sunila Gollapudi

Practical Machine Learning Book PDF
✏Book Title : Practical Machine Learning
✏Author : Sunila Gollapudi
✏Publisher : Packt Publishing Ltd
✏Release Date : 2016-01-30
✏Pages : 468
✏ISBN : 9781784394011
✏Available Language : English, Spanish, And French

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✏Practical Machine Learning Book Summary : Tackle the real-world complexities of modern machine learning with innovative, cutting-edge, techniques About This Book Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark Comprehensive practical solutions taking you into the future of machine learning Go a step further and integrate your machine learning projects with Hadoop Who This Book Is For This book has been created for data scientists who want to see machine learning in action and explore its real-world application. With guidance on everything from the fundamentals of machine learning and predictive analytics to the latest innovations set to lead the big data revolution into the future, this is an unmissable resource for anyone dedicated to tackling current big data challenges. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately. What You Will Learn Implement a wide range of algorithms and techniques for tackling complex data Get to grips with some of the most powerful languages in data science, including R, Python, and Julia Harness the capabilities of Spark and Hadoop to manage and process data successfully Apply the appropriate machine learning technique to address real-world problems Get acquainted with Deep learning and find out how neural networks are being used at the cutting-edge of machine learning Explore the future of machine learning and dive deeper into polyglot persistence, semantic data, and more In Detail Finding meaning in increasingly larger and more complex datasets is a growing demand of the modern world. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. Machine learning uses complex algorithms to make improved predictions of outcomes based on historical patterns and the behaviour of data sets. Machine learning can deliver dynamic insights into trends, patterns, and relationships within data, immensely valuable to business growth and development. This book explores an extensive range of machine learning techniques uncovering hidden tricks and tips for several types of data using practical and real-world examples. While machine learning can be highly theoretical, this book offers a refreshing hands-on approach without losing sight of the underlying principles. Inside, a full exploration of the various algorithms gives you high-quality guidance so you can begin to see just how effective machine learning is at tackling contemporary challenges of big data. This is the only book you need to implement a whole suite of open source tools, frameworks, and languages in machine learning. We will cover the leading data science languages, Python and R, and the underrated but powerful Julia, as well as a range of other big data platforms including Spark, Hadoop, and Mahout. Practical Machine Learning is an essential resource for the modern data scientists who want to get to grips with its real-world application. With this book, you will not only learn the fundamentals of machine learning but dive deep into the complexities of real world data before moving on to using Hadoop and its wider ecosystem of tools to process and manage your structured and unstructured data. You will explore different machine learning techniques for both supervised and unsupervised learning; from decision trees to Naive Bayes classifiers and linear and clustering methods, you will learn strategies for a truly advanced approach to the statistical analysis of data. The book also explores the cutting-edge advancements in machine learning, with worked examples and guidance on deep learning and reinforcement learning, providing you with practical demonstrations and samples that help take the theory–and mystery–out of even the most advanced machine learning methodologies. Style and approach A practical data science tutorial designed to give you an insight into the practical application of machine learning, this book takes you through complex concepts and tasks in an accessible way. Featuring information on a wide range of data science techniques, Practical Machine Learning is a comprehensive data science resource.

Practical Machine Learning With H2o Book PDF
✏Book Title : Practical Machine Learning with H2O
✏Author : Darren Cook
✏Publisher : "O'Reilly Media, Inc."
✏Release Date : 2016-12-05
✏Pages : 300
✏ISBN : 9781491964576
✏Available Language : English, Spanish, And French

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✏Practical Machine Learning with H2O Book Summary : Learn how to construct machine learning and data analysis scalable for big data using H2O software, using sample data sets and several machine-learning techniques including deep learning, random forests, unsupervised learning and ensemble learning.

📒Python Machine Learning ✍ Sebastian Raschka

Python Machine Learning Book PDF
✏Book Title : Python Machine Learning
✏Author : Sebastian Raschka
✏Publisher : Packt Publishing Ltd
✏Release Date : 2017-09-20
✏Pages : 622
✏ISBN : 9781787126022
✏Available Language : English, Spanish, And French

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✏Python Machine Learning Book Summary : Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. About This Book Second edition of the bestselling book on Machine Learning A practical approach to key frameworks in data science, machine learning, and deep learning Use the most powerful Python libraries to implement machine learning and deep learning Get to know the best practices to improve and optimize your machine learning systems and algorithms Who This Book Is For If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential and unmissable resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for developers and data scientists who want to teach computers how to learn from data. What You Will Learn Understand the key frameworks in data science, machine learning, and deep learning Harness the power of the latest Python open source libraries in machine learning Explore machine learning techniques using challenging real-world data Master deep neural network implementation using the TensorFlow library Learn the mechanics of classification algorithms to implement the best tool for the job Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Delve deeper into textual and social media data using sentiment analysis In Detail Machine learning is eating the software world, and now deep learning is extending machine learning. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschka's bestselling book, Python Machine Learning. Thoroughly updated using the latest Python open source libraries, this book offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. Fully extended and modernized, Python Machine Learning Second Edition now includes the popular TensorFlow deep learning library. The scikit-learn code has also been fully updated to include recent improvements and additions to this versatile machine learning library. Sebastian Raschka and Vahid Mirjalili's unique insight and expertise introduce you to machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. By the end of the book, you'll be ready to meet the new data analysis opportunities in today's world. If you've read the first edition of this book, you'll be delighted to find a new balance of classical ideas and modern insights into machine learning. Every chapter has been critically updated, and there are new chapters on key technologies. You'll be able to learn and work with TensorFlow more deeply than ever before, and get essential coverage of the Keras neural network library, along with the most recent updates to scikit-learn. Style and Approach Python Machine Learning Second Edition takes a practical, hands-on coding approach so you can learn about machine learning by coding with Python. This book moves fluently between the theoretical principles of machine learning and the practical details of implementation with Python.

Python Machine Learning For Beginners Book PDF
✏Book Title : Python Machine Learning for Beginners
✏Author : Ai Publishing
✏Publisher :
✏Release Date : 2020-10-23
✏Pages : 302
✏ISBN : 1734790156
✏Available Language : English, Spanish, And French

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✏Python Machine Learning for Beginners Book Summary : Python Machine Learning for BeginnersMachine Learning (ML) and Artificial Intelligence (AI) are here to stay. Yes, that's right. Based on a significant amount of data and evidence, it's obvious that ML and AI are here to stay.Consider any industry today. The practical applications of ML are really driving business results. Whether it's healthcare, e-commerce, government, transportation, social media sites, financial services, manufacturing, oil and gas, marketing and salesYou name it. The list goes on. There's no doubt that ML is going to play a decisive role in every domain in the future.But what does a Machine Learning professional do?A Machine Learning specialist develops intelligent algorithms that learn from data and also adapt to the data quickly. Then, these high-end algorithms make accurate predictions. Python Machine Learning for Beginners presents you with a hands-on approach to learn ML fast.How Is This Book Different?AI Publishing strongly believes in learning by doing methodology. With this in mind, we have crafted this book with care. You will find that the emphasis on the theoretical aspects of machine learning is equal to the emphasis on the practical aspects of the subject matter.You'll learn about data analysis and visualization in great detail in the first half of the book. Then, in the second half, you'll learn about machine learning and statistical models for data science.Each chapter presents you with the theoretical framework behind the different data science and machine learning techniques, and practical examples illustrate the working of these techniques.When you buy this book, your learning journey becomes so much easier. The reason is you get instant access to all the related learning material presented with this book--references, PDFs, Python codes, and exercises--on the publisher's website. All this material is available to you at no extra cost. You can download the ML datasets used in this book at runtime, or you can access them via the Resources/Datasets folder.You'll also find the short course on Python programming in the second chapter immensely useful, especially if you are new to Python. Since this book gives you access to all the Python codes and datasets, you only need access to a computer with the internet to get started. The topics covered include: Introduction and Environment Setup Python Crash Course Python NumPy Library for Data Analysis Introduction to Pandas Library for Data Analysis Data Visualization via Matplotlib, Seaborn, and Pandas Libraries Solving Regression Problems in ML Using Sklearn Library Solving Classification Problems in ML Using Sklearn Library Data Clustering with ML Using Sklearn Library Deep Learning with Python TensorFlow 2.0 Dimensionality Reduction with PCA and LDA Using Sklearn Click the BUY NOW button to start your Machine Learning journey.

📒Machine Learning ✍ Andrew Park

Machine Learning Book PDF
✏Book Title : Machine Learning
✏Author : Andrew Park
✏Publisher :
✏Release Date : 2020-11-14
✏Pages : 250
✏ISBN : 1914167058
✏Available Language : English, Spanish, And French

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✏Machine Learning Book Summary : Master The World Of Machine Learning And Data Science With This Comprehensive 2-in-1 bundleIf you want to learn more about Machine Learning and Data Science or how to master them with Python quickly and easily, then keep reading. Data Science and Machine Learning are one of the biggest buzzwords in the business world nowadays. Many businesses know the importance of collecting information, but as they can collect so much data in a short period, the real question is: "what is the next step?" Data Science includes all the different steps that you take with the data: collecting and cleaning them, analyzing them, applying Machine Learning algorithms and models, and then presenting your findings from the analysis with some good Data Visualizations. Machines and automation represent a huge part of our daily life. They are becoming part of our experience, and existence. Artificial Intelligence is currently one of the most thriving fields any programmer would wish to delve into, and for a good reason: this is the future! Simply put, Machine Learning is about teaching machines to think and make decisions as we would. The difference between the way machines learn and the way we do is that while for the most part we learn from experiences, machines learn from data. In book one, PYTHON MACHINE LEARNING, you will learn: What is Machine Learning and how it is applied in real-world situations Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence Machine learning training models, Regression techniques and Linear Regression in Python How to use Lists and Modules in Python The 12 essential libraries for Machine Learning in Python Artificial Neural Networks And Much More! In book two, PYTHON DATA SCIENCE, you will learn: What Data Science is all about and why so many companies are using it to give them a competitive edge. Why Python and how to use it to implement Data Science The main Data Structures & Object-Oriented Programming, Functions and Modules in Python with practical codes and exercises The 7 most important algorithms and models in Data Science Data Aggregation, Group Operations, Databases and Data in the Cloud 9 important Data Mining techniques in Data Science And So Much More! Where most books only focus on how collecting and cleaning the data, this book goes further, providing guidance on how to perform a proper analysis in order to extract precious information that may be vital for a business. Don't miss the opportunity to master the key points of Machine Learning technology and understand how researchers are breaking the boundaries of Data Science to mimic human intelligence in machines. Even if some Machine Learning concepts and algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way. Understanding Machine Learning and Data Science is easier than it looks. You just need the right guidance. And this bundle provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the techniques to manipulate and process datasets, the principles of Python programming, and its most important real-world applications. Would You Like To Know More?Scroll Up and Click the BUY NOW Button to Get Your Copy!

Pragmatic Machine Learning With Python Book PDF
✏Book Title : Pragmatic Machine Learning with Python
✏Author : Avishek Nag
✏Publisher : BPB Publications
✏Release Date : 2020-04-30
✏Pages : 340
✏ISBN : 9789389845365
✏Available Language : English, Spanish, And French

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✏Pragmatic Machine Learning with Python Book Summary : An easy-to-understand guide to learn practical Machine Learning techniques with Mathematical foundations KEY FEATURES - A balanced combination of underlying mathematical theories & practical examples with Python code - Coverage of latest topics like multi-label classification, Text Mining, Doc2Vec, Word2Vec, XMeans clustering, unsupervised outlier detection, techniques to deploy ML models in production-grade systems with PMML, etc - Coverage of sufficient & relevant visualization techniques specific to any topic DESCRIPTION This book will be ideal for working professionals who want to learn Machine Learning from scratch. The first chapter will be an introductory chapter to make readers comfortable with the idea of Machine Learning and the required mathematical theories. There will be a balanced combination of underlying mathematical theories corresponding to any Machine Learning topic and its implementation using Python. Most of the implementations will be based on ‘scikit-learn,’ but other Python libraries like ‘Gensim’ or ‘PyTorch’ will also be used for some topics like text analytics or deep learning. The book will be divided into chapters based on primary Machine Learning topics like Classification, Regression, Clustering, Deep Learning, Text Mining, etc. The book will also explain different techniques of putting Machine Learning models into production-grade systems using Big Data or Non-Big Data flavors and standards for exporting models. WHAT WILL YOU LEARN - Get familiar with practical concepts of Machine Learning from ground zero - Learn how to deploy Machine Learning models in production - Understand how to do “Data Science Storytelling” - Explore the latest topics in the current industry about Machine Learning WHO THIS BOOK IS FOR This book would be ideal for experienced Software Professionals who are trying to get into the field of Machine Learning. Anyone who wishes to Learn Machine Learning concepts and models in the production lifecycle. TABLE OF CONTENTS 1. Introduction to Machine Learning & Mathematical preliminaries 2. Classification 3. Regression 4. Clustering 5. Deep Learning & Neural Networks 6. Miscellaneous Unsupervised Learning 7. Text Mining 8. Machine Learning models in production 9. Case Studies & Data Science Storytelling

Practical Machine Learning And Image Processing Book PDF
✏Book Title : Practical Machine Learning and Image Processing
✏Author : Himanshu Singh
✏Publisher : Apress
✏Release Date : 2019-02-26
✏Pages : 169
✏ISBN : 9781484241493
✏Available Language : English, Spanish, And French

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✏Practical Machine Learning and Image Processing Book Summary : Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application. What You Will Learn Discover image-processing algorithms and their applications using Python Explore image processing using the OpenCV library Use TensorFlow, scikit-learn, NumPy, and other libraries Work with machine learning and deep learning algorithms for image processing Apply image-processing techniques to five real-time projects Who This Book Is For Data scientists and software developers interested in image processing and computer vision.

📒Python For Data Science ✍ Erick Thompson

Python For Data Science Book PDF
✏Book Title : Python for Data Science
✏Author : Erick Thompson
✏Publisher : Charlie Creative Lab
✏Release Date : 2020-10-30
✏Pages : 266
✏ISBN : 1801131872
✏Available Language : English, Spanish, And French

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✏Python for Data Science Book Summary : Are you looking for a crash course that will help you learn Python? Do you want to master data science using Python? If yes, then keep reading! Python is one of the most popular programming languages in the word in 2020 and specially for data science. Every day people use it to do cool things like Automation, they use it in Artificial Intelligence, Machine Learning, as well as Building Applications and Websites like Instagram and Dropbox. YouTube, Pinterest, and SurveyMonkey are all built on Python. So if you are looking for a trendy job, like data scientist, Python is for you. This is a Python guide with 2 Books in 1: Python crash course Python for data analysis Python has seen an explosion in popularity in recent years, driven by several aspects that make it an incredibly versatile and intuitive language. Moreover, data analysis plays a significant job in numerous parts of your regular day to day existence today. Organizations use information to Understand Their Customer Needs and produce the Best Possible Product or Service. Python Programming Language is one of the best framework with regards to information examination. Data Scientist is the most requested job of the 21st century and Python is the most popular programming language of the 21st century. So it's pretty obvious that anyone have skills in both Data Science and Python will be in great demand in industry. You needn't bother with an exhausting and costly reading material. This guide is the best one for every readers. This guide covers: The world of data science technologies Application of machine learning Data scientist: the sexiest job in the 21st century Learning Python from scratch Data analysis with Python NumPy for numerical data processing Data visualization with Python Projects on Python And much more! Despite its simplicity, Python is also sturdy and robust enough to carry out complex scientific and mathematical tasks. Python has been designed with features that drastically simplify the visualization and analysis of data, and Python is also the go-to choice for the creation of machine learning models and artificial intelligence. Be it machine learning, data analytics, data processing, web development, enterprise software development or taking the photo of Blackhole: Python is everywhere. Beloved by the data scientists and new generation developers, Pyhton will eat the word! Ready to get started? Click the BUY NOW button!

📒Python For Data Analysis ✍ Erick Thompson

Python For Data Analysis Book PDF
✏Book Title : Python for Data Analysis
✏Author : Erick Thompson
✏Publisher : Charlie Creative Lab
✏Release Date : 2020-11-11
✏Pages : 126
✏ISBN : 1801235147
✏Available Language : English, Spanish, And French

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✏Python for Data Analysis Book Summary : Do you want to master data using python? If yes, then keep reading! Data analysis plays a significant job in numerous parts of your regular day to day existence today. From the second you wake up, you cooperate with information at various levels. A great deal of significant choices are made dependent on information examination. None of the organizations would capacity and run effectively without individuals who realize how to utilize ace this incredible asset. Organizations use information to Understand Their Customer Needs and produce the Best Possible Product or Service. Python Programming Language is one of the best framework with regards to information examination, and in the event that you are considering starting your own business some time or another or as of now have one, this is certainly a device you should comprehend and utilize. Data Scientist is the most requested job of the 21st century and Python is the most popular programming language of the 21st century. The average salary of a Data Scientist is around 120 thousand dollars per year and the average salary of a Pythton Developer is around 100 thousand dollars. So it's pretty obvious that anyone have skills in both Data Science and Python will be in great demand in industry. You needn't bother with an exhausting and costly reading material. This book is the best one for every readers. This book covers: - Introduction to Python and data analysis - Python basics - Python history - Installing Python - Data analysis with Python - NumPy for numerical data processing - Data visualization with Python - Machine learning with Python And much more! Be it Data Processing, Data Analytics, Data Modeling, Data Visualization, Data Predictive, Machine Learning, or taking the photo of Blackhole: Python is everywhere and it is the most powerful programming language of 21st century. Beloved by the data scientists and new generation developers, Pyhton will eat the word! Ready to get started? Click "Buy Now"!

Data Science For Beginners Book PDF
✏Book Title : Data Science for Beginners
✏Author : Andrew Park
✏Publisher :
✏Release Date : 2020-11-10
✏Pages : 482
✏ISBN : 1914167007
✏Available Language : English, Spanish, And French

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✏Data Science for Beginners Book Summary : Master the world of Python, Data Analysis, Machine Learning and Data Science with this comprehensive 4-in-1 bundle.Would you like to become a Python geek? Or do you want to learn more about the fascinating world of Machine Learning an Data Science? Well, the solution is right in front of you! With this bundle in your hands, you'll go from beginner to pro in no time. These books and guides are specifically designed for people that have little or no prior knowledge about Python Programming. Everything inside is designed to be step-by-step, so you can have an easier time understanding the concepts around it. This comprehensive bundle contains everything you'll need to know to successfully implement Data Science techniques and Machine Learning algorithms through Python. From basic tutorials and exercises to expert coding techniques. In book one, PYTHON FOR BEGINNERS, you will learn: How to install Python What are the different Python Data Types, Variables and Basic Operators Data Structures, Functions and Files Conditional and Loops in Python Object-Oriented Programming (OOP), Inheritance and Polymorphism Essential Programming Tools and Exception Handling And Much More! In book two, PYTHON FOR DATA ANALYSIS, you will: Learn the Fundamentals of Data Analysis and why Businesses are Investing in this Sector Master the 5 steps of a Proper Data Analysis Know what are the 7 Python libraries that make Python one of the best choices for Data Analysis Learn how Data Visualization and Matplotlib can help You to Understand the Data you are Working with Learn about some of the Main Industries that are Using Data to Improve their Business with 14 real-world Applications And Much More! In book three, PYTHON MACHINE LEARNING, you will understand: What are the Basics of Machine Learning and how it is Applied in real-world Situations What is the Difference between Machine Learning, Deep Learning, and Artificial Intelligence How to Implement Machine Learning Training Models, Regression Techniques and Linear Regression in Python How to use Lists and Modules in Python What are the 12 Essential Libraries for Machine Learning in Python How to Correctly use Artificial Neural Networks And Much More! And in book four, PYTHON DATA SCIENCE, you will discover: What Data Science is all about and why so many Companies are Using it to get a Competitive Edge. The main Data Structures & Object-Oriented Programming, Functions and Modules in Python with Practical Codes and Exercises The 7 Most Important Algorithms and Models in Data Science Data Aggregation, Group Operations, Databases and Data in the Cloud 9 important Data Mining techniques in Data Science And So Much More! It doesn't matter if you are a beginner, or you never have coded before. This guide will slowly ease you into the world of Data Science. While most of the other similar books put the focus on theory and complicated concepts, this one is designed specifically for beginners. Furthermore, topics are carefully selected to give you broad exposure, while not overwhelming you with too much information. Also, unlike the majority of books, the outputs of ALL the examples are provided immediately so you do not have to wait till you have access to your computer to test the examples. Ready to Master Python, Machine Learning and Data Science?Scroll Up and Click the BUY NOW Button to Get Your Copy!

Building Machine Learning Systems With Python Book PDF
✏Book Title : Building Machine Learning Systems with Python
✏Author : Luis Pedro Coelho
✏Publisher : Packt Publishing Ltd
✏Release Date : 2018-07-31
✏Pages : 406
✏ISBN : 9781788622226
✏Available Language : English, Spanish, And French

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✏Building Machine Learning Systems with Python Book Summary : Get more from your data by creating practical machine learning systems with Python Key Features Develop your own Python-based machine learning system Discover how Python offers multiple algorithms for modern machine learning systems Explore key Python machine learning libraries to implement in your projects Book Description Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems. Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you’ll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems. By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks. What you will learn Build a classification system that can be applied to text, images, and sound Employ Amazon Web Services (AWS) to run analysis on the cloud Solve problems related to regression using scikit-learn and TensorFlow Recommend products to users based on their past purchases Understand different ways to apply deep neural networks on structured data Address recent developments in the field of computer vision and reinforcement learning Who this book is for Building Machine Learning Systems with Python is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. You will use Python's machine learning capabilities to develop effective solutions. Prior knowledge of Python programming is expected.

Python Machine Learning For Beginners Book PDF
✏Book Title : Python Machine Learning for Beginners
✏Author : Peter Treu
✏Publisher : Charlie Creative Lab
✏Release Date : 2020-11-05
✏Pages : 138
✏ISBN : 180120439X
✏Available Language : English, Spanish, And French

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✏Python Machine Learning for Beginners Book Summary : Do you Want to learn more about Python Machine Learning ?.... then read on. Machine learning stems from this question: Can a computer go beyond anything we can order to do and learn by itself to do a specific task? Can a laptop surprise us? Instead of having programmers carefully and manually writing a set of data processing rules, can a computer automatically learn these rules by merely looking at the data? This question paves the way for a new programming paradigm. In classical programming, on which symbolic artificial intelligence is based, human beings insert rules (the program) and the data to be processed according to these rules and obtain answers. Humans enter data and expected responses based on that data with machine learning, and the computer identifies the practices. These rules can then be applied to other data to produce different, original answers. A machine learning system is trained and not programmed. He is presented with numerous examples relevant to a given task. In these examples, he finds a statistical structure that ultimately allows him to produce the rules for the task's automation. For example, to automate tagging vacation photographs, many examples of images already tagged by humans could be presented to a machine learning system. The system would be tasked with learning the statistical rules based on associating individual images with specific tags. Machine learning is closely related to statistics, but it differs from them in many important ways. Unlike statistics, machine learning tends to operate with large and complex datasets (such as a dataset of millions of images, each consisting of tens of thousands of pixels) for which classical statistical analysis such as Bayesian analysis would not be usable. . As a result, machine learning, and especially deep learning, exhibits somewhat limited mathematical theory - sometimes too much - and is more technical than mathematical. It is a practical discipline in which ideas often prove more empirically than theoretical. In this Book you will learning: What is Data Science and Deep Learning? Data Science and Applications Probability - Fundamental - Statistics Understanding the Fundamentals of iMachine Learning Types of MachineiLearning What is iPython? SettingiUp the Environment in Python K - Nearest Neighbor Algorithms Means Clustering Neural Networks - Linear Classifiers While most books focus on advanced predictive models, this book begins to explain the basic concepts and how to correctly implement Data Science and Machine Learning, with practical examples and simple coding scripts. This guide provides the necessary knowledge in a practical way. You will learn the steps of Machine Learning, how to implement them in Python, and the most important applications in the real world. Would you like to know more? Download the Book, Python Machine Learning. Scroll to the top of the page and click the "Buy now" button to get your copy now.

📒Python Machine Learning ✍ Frank Millstein

Python Machine Learning Book PDF
✏Book Title : Python Machine Learning
✏Author : Frank Millstein
✏Publisher : Frank Millstein
✏Release Date : 2020-07-05
✏Pages : 128
✏ISBN :
✏Available Language : English, Spanish, And French

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✏Python Machine Learning Book Summary : Python Machine Learning Machine learning is the science of getting machines and computers to act and learn on their own without being programmed explicitly. In just the past decade, this field has given us practical speech recognition, self-driving cars, greatly improved understanding of the overall human genome, effective web search and much more. Therefore, there is no wondering why machine learning is so pervasive today. In this book, you will learn more about interpreting machine learning techniques using Python. You will also gain practice as you implement the most popular machine learning techniques on some real-world examples and you will learn both about the theoretical and practical machine learning implementation using Python's machine learning libraries. At the end of the book, you will be able to cope with more complex machine learning issues solving your own problems using Python and its libraries specifically crafted for machine learning. Here Is A Preview Of What You’ll Learn Here… Basics behind machine learning techniques Different machine learning algorithms Fundamental machine learning applications and their importance Getting started with machine learning in Python, installing and starting SciPy Loading data and importing different libraries Data summarization and data visualization Evaluation of machine learning models and making predictions Most commonly used machine learning algorithms, linear and logistic regression, decision trees support vector machines, k-nearest neighbors, random forests Solving multi-clasisfication problems Data visualization with Matplotlib and data transformation with Pandas and Scikit-learn Solving multi-label classification problems And much, much more... Get this book NOW and learn more about Machine Learning with Python!

📒Practical Data Analysis ✍ Hector Cuesta

Practical Data Analysis Book PDF
✏Book Title : Practical Data Analysis
✏Author : Hector Cuesta
✏Publisher : Packt Publishing Ltd
✏Release Date : 2016-09-30
✏Pages : 338
✏ISBN : 9781785286667
✏Available Language : English, Spanish, And French

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✏Practical Data Analysis Book Summary : A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Python For Data Analysis Book PDF
✏Book Title : Python for Data Analysis
✏Author : Jason Test
✏Publisher : Independently Published
✏Release Date : 2020-11-14
✏Pages : 238
✏ISBN : 9918951591
✏Available Language : English, Spanish, And French

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✏Python for Data Analysis Book Summary : Master the best methods for PYTHON. Learn how to programming as a pro and get positive ROI in 7 days with data science and machine learning Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your business thanks to the web applications? If so, keep reading: this bundle book is for you! Today, thanks to computer programming and PYTHON we can work with sophisticated machines that can study human behavior and identify underlying human behavioral patterns. Scientists can predict effectively what products and services consumers are interested in. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. PYTHON FOR DATA ANALYSIS will introduce you many selected tips and breaking down the basics of coding. You will discover as a beginner the world of data science, machine learning and artificial intelligence. The description of each topic is crystal-clear and you can easily practice with related exercises. Examples and step-by-step guides will guide you during the code-writing learning process. The following list is just a tiny fraction of what you will learn in this bundle: PYTHON FOR DATA SCIENCE ✅ The basics of Python programming ✅ Differences among programming languages: Vba, SQL, R, Python ✅ 3 reasons why Python is fundamental for Data Science ✅ Introduction to some Python libraries like NumPy, Pandas, Matplotlib, ✅ Python design patterns ✅ 3 step system why Python is fundamental for Data Science ✅Optimal tools and techniques for data visualization ✅ Analysis of popular Python projects templates ✅ Game creation with Pyhton PYTHON CRASH COURSE ✅ A Proven Method to Write your First Program in 7 Days ✅ 3 Common Mistakes to Avoid when You Start Coding ✅ Fit Python Data Analysis to your business ✅ A Simple Strategy to Write Clean, Understandable and Flexible Codes ✅ The One Thing You Need to Debug your Codes in Python ✅ 5 Practical exercises to start programming ✅ 7 Most effective Machine Learning Algorithms Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. Today is the best day to start programming like a pro. It's never too late to learn a coding language, whether you're 19 or 50! If you really wish to learn Python and master its language, please click the BUY NOW button.

Building Machine Learning Systems With Python Third Edition Book PDF
✏Book Title : Building Machine Learning Systems with Python Third Edition
✏Author : Luis Coelho
✏Publisher :
✏Release Date : 2018
✏Pages : 406
✏ISBN : OCLC:1105784411
✏Available Language : English, Spanish, And French

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✏Building Machine Learning Systems with Python Third Edition Book Summary : Get more from your data by creating practical machine learning systems with Python Key Features Develop your own Python-based machine learning system Discover how Python offers multiple algorithms for modern machine learning systems Explore key Python machine learning libraries to implement in your projects Book Description Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems. Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you'll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems. By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks. What you will learn Build a classification system that can be applied to text, images, and sound Employ Amazon Web Services (AWS) to run analysis on the cloud Solve problems related to regression using scikit-learn and TensorFlow Recommend products to users based on their past purchases Understand different ways to apply deep neural networks on structured data Address recent developments in the field of computer vision and reinforcement learning Who this book is for Building Machine Learning Systems with Python is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. You will use Python's machine learning capabilities to develop effective solutions. Prior knowledge of Python progr ...

Large Scale Machine Learning With Python Book PDF
✏Book Title : Large Scale Machine Learning with Python
✏Author : Bastiaan Sjardin
✏Publisher : Packt Publishing Ltd
✏Release Date : 2016-08-03
✏Pages : 420
✏ISBN : 9781785888021
✏Available Language : English, Spanish, And French

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✏Large Scale Machine Learning with Python Book Summary : Learn to build powerful machine learning models quickly and deploy large-scale predictive applications About This Book Design, engineer and deploy scalable machine learning solutions with the power of Python Take command of Hadoop and Spark with Python for effective machine learning on a map reduce framework Build state-of-the-art models and develop personalized recommendations to perform machine learning at scale Who This Book Is For This book is for anyone who intends to work with large and complex data sets. Familiarity with basic Python and machine learning concepts is recommended. Working knowledge in statistics and computational mathematics would also be helpful. What You Will Learn Apply the most scalable machine learning algorithms Work with modern state-of-the-art large-scale machine learning techniques Increase predictive accuracy with deep learning and scalable data-handling techniques Improve your work by combining the MapReduce framework with Spark Build powerful ensembles at scale Use data streams to train linear and non-linear predictive models from extremely large datasets using a single machine In Detail Large Python machine learning projects involve new problems associated with specialized machine learning architectures and designs that many data scientists have yet to tackle. But finding algorithms and designing and building platforms that deal with large sets of data is a growing need. Data scientists have to manage and maintain increasingly complex data projects, and with the rise of big data comes an increasing demand for computational and algorithmic efficiency. Large Scale Machine Learning with Python uncovers a new wave of machine learning algorithms that meet scalability demands together with a high predictive accuracy. Dive into scalable machine learning and the three forms of scalability. Speed up algorithms that can be used on a desktop computer with tips on parallelization and memory allocation. Get to grips with new algorithms that are specifically designed for large projects and can handle bigger files, and learn about machine learning in big data environments. We will also cover the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python. Style and Approach This efficient and practical title is stuffed full of the techniques, tips and tools you need to ensure your large scale Python machine learning runs swiftly and seamlessly. Large-scale machine learning tackles a different issue to what is currently on the market. Those working with Hadoop clusters and in data intensive environments can now learn effective ways of building powerful machine learning models from prototype to production. This book is written in a style that programmers from other languages (R, Julia, Java, Matlab) can follow.

Python Real World Machine Learning Book PDF
✏Book Title : Python Real World Machine Learning
✏Author : Prateek Joshi
✏Publisher : Packt Publishing Ltd
✏Release Date : 2016-11-14
✏Pages : 941
✏ISBN : 9781787120679
✏Available Language : English, Spanish, And French

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✏Python Real World Machine Learning Book Summary : Learn to solve challenging data science problems by building powerful machine learning models using Python About This Book Understand which algorithms to use in a given context with the help of this exciting recipe-based guide This practical tutorial tackles real-world computing problems through a rigorous and effective approach Build state-of-the-art models and develop personalized recommendations to perform machine learning at scale Who This Book Is For This Learning Path is for Python programmers who are looking to use machine learning algorithms to create real-world applications. It is ideal for Python professionals who want to work with large and complex datasets and Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. Experience with Python, Jupyter Notebooks, and command-line execution together with a good level of mathematical knowledge to understand the concepts is expected. Machine learning basic knowledge is also expected. What You Will Learn Use predictive modeling and apply it to real-world problems Understand how to perform market segmentation using unsupervised learning Apply your new-found skills to solve real problems, through clearly-explained code for every technique and test Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms Increase predictive accuracy with deep learning and scalable data-handling techniques Work with modern state-of-the-art large-scale machine learning techniques Learn to use Python code to implement a range of machine learning algorithms and techniques In Detail Machine learning is increasingly spreading in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. Machine learning is transforming the way we understand and interact with the world around us. In the first module, Python Machine Learning Cookbook, you will learn how to perform various machine learning tasks using a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms. The second module, Advanced Machine Learning with Python, is designed to take you on a guided tour of the most relevant and powerful machine learning techniques and you'll acquire a broad set of powerful skills in the area of feature selection and feature engineering. The third module in this learning path, Large Scale Machine Learning with Python, dives into scalable machine learning and the three forms of scalability. It covers the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python. This Learning Path will teach you Python machine learning for the real world. The machine learning techniques covered in this Learning Path are at the forefront of commercial practice. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Python Machine Learning Cookbook by Prateek Joshi Advanced Machine Learning with Python by John Hearty Large Scale Machine Learning with Python by Bastiaan Sjardin, Alberto Boschetti, Luca Massaron Style and approach This course is a smooth learning path that will teach you how to get started with Python machine learning for the real world, and develop solutions to real-world problems. Through this comprehensive course, you'll learn to create the most effective machine learning techniques from scratch and more!

Python Real World Data Science Book PDF
✏Book Title : Python Real World Data Science
✏Author : Dusty Phillips
✏Publisher : Packt Publishing Ltd
✏Release Date : 2016-06-10
✏Pages : 1255
✏ISBN : 9781786468413
✏Available Language : English, Spanish, And French

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✏Python Real World Data Science Book Summary : Unleash the power of Python and its robust data science capabilities About This Book Unleash the power of Python 3 objects Learn to use powerful Python libraries for effective data processing and analysis Harness the power of Python to analyze data and create insightful predictive models Unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Who This Book Is For Entry-level analysts who want to enter in the data science world will find this course very useful to get themselves acquainted with Python's data science capabilities for doing real-world data analysis. What You Will Learn Install and setup Python Implement objects in Python by creating classes and defining methods Get acquainted with NumPy to use it with arrays and array-oriented computing in data analysis Create effective visualizations for presenting your data using Matplotlib Process and analyze data using the time series capabilities of pandas Interact with different kind of database systems, such as file, disk format, Mongo, and Redis Apply data mining concepts to real-world problems Compute on big data, including real-time data from the Internet Explore how to use different machine learning models to ask different questions of your data In Detail The Python: Real-World Data Science course will take you on a journey to become an efficient data science practitioner by thoroughly understanding the key concepts of Python. This learning path is divided into four modules and each module are a mini course in their own right, and as you complete each one, you'll have gained key skills and be ready for the material in the next module. The course begins with getting your Python fundamentals nailed down. After getting familiar with Python core concepts, it's time that you dive into the field of data science. In the second module, you'll learn how to perform data analysis using Python in a practical and example-driven way. The third module will teach you how to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis to more complex data types including text, images, and graphs. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. In the final module, we'll discuss the necessary details regarding machine learning concepts, offering intuitive yet informative explanations on how machine learning algorithms work, how to use them, and most importantly, how to avoid the common pitfalls. Style and approach This course includes all the resources that will help you jump into the data science field with Python and learn how to make sense of data. The aim is to create a smooth learning path that will teach you how to get started with powerful Python libraries and perform various data science techniques in depth.

📒Python Programming ✍ Jason Test

Python Programming Book PDF
✏Book Title : Python Programming
✏Author : Jason Test
✏Publisher :
✏Release Date : 2020-10-15
✏Pages : 360
✏ISBN : 9918951265
✏Available Language : English, Spanish, And French

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✏Python Programming Book Summary : Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your business thanks to the web applications? If so, keep reading: this bundle book is for you! Finally on launch the most complete Python guide with 3 Manuscripts in 1 book: 1-Python for beginners 2-Python for Data Science 3-Python Crash Course Python will introduce you many selected practices for coding . You will discover as a beginner the world of data science, machine learning and artificial intelligence. The following list is just a tiny fraction of what you will learn in this collection bundle. 1) Python for beginners ✓ The basics of Python programming ✓ Differences among programming languages ✓ Vba, SQL, R, Python ✓ Game creation with Pyhton ✓ Easy-to-follow steps for reading and writing codes. ✓ Control flow statements and Error handling ✓ 3 best strategies with NumPy, Pandas, Matplotlib 2) Python for Data science ◆ 3 reasons why Python is fundamental for Data Science ◆ Python design patterns ◆ How to use Python Data Analysis in your business ◆ Data visualization optimal tools and techniques ◆ Analysis of popular Python projects templates ◆ How to set up the Python environment for Data Science ◆ Most important Machine Learning Algorithms ◆ How to leverage Data Science in the Cloud 3) Python Crash Course - A Proven Method to Write your First Program in 7 Days - 5 Common Mistakes to Avoid when You Start Coding - A Simple Strategy to Write Clean, Understandable and Flexible Codes - The One Thing You Need to Debug your Codes in Python - 5 Practical exercises to start programming Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. Examples and step-by-step guides will guide you during the code-writing learning process. The description of each topic is crystal-clear and you can easily practice with related exercises. You will also learn all the best tricks of writing codes with point by point descriptions of the code elements. If you really wish to to learn Python and master its language, please click the BUY NOW button.

📒Python Programming ✍ Andrew Park

Python Programming Book PDF
✏Book Title : Python Programming
✏Author : Andrew Park
✏Publisher :
✏Release Date : 2020-08-22
✏Pages : 304
✏ISBN : 9798677571909
✏Available Language : English, Spanish, And French

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✏Python Programming Book Summary : If you want to learn Python in one week (or less) and learn it well, with useful applications to Data Analysis, Machine Learning and Data Science, then keep reading. Python is one of the most beloved programming languages in any circle of programmers. Software engineers, hackers, and Data Scientists alike are in love with the versatility that Python has to offer. Besides, the Object-Oriented feature of Python coupled with its flexibility is also one of the major attractions for this language. That's the reason why Python is a perfect fit with Data Analysis, Machine Learning and Data Science. Data is the future. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations. The goal of this 4-in-1 bundle is simple: explaining everything you need to know to Master Python. With a special emphasis on the main steps that are needed to correctly implement Data Analysis and Machine Learning algorithms, In manuscript one, Python for Beginners, you will learn: How to install Python What are the different Python Data Types and Variables Basic Operators of Python Language Data Structures and Functions Conditional and Loops in Python And Much More! In manuscript two, Python Advanced Guide, you will master: Object-Oriented Programming (OOP), Inheritance and Polymorphism Essential Programming Tools Exception Handling Working with Files And Much More! In manuscript three, Python for Data Analysis, you will learn: What Data Analysis is all about and why businesses are investing in this sector The 5 steps of a Data Analysis The 7 Python libraries that make Python one of the best choices for Data Analysis Pandas, Jupyter and PyTorch And Much More! In manuscript four, Applications to Data Science, you will understand: How Data Visualization and Matplotlib can help you to understand the data you are working with. Neural Networks Decision Trees What industries are using data to improve their business with 14 real-world applications And So Much More! Where most books about Python programming are theoretical and have few or little practical examples, this book provides lots of simple, step-by-step examples and illustrations that are used to underline key concepts and help improve your understanding. Furthermore, topics are carefully selected to give you broad exposure to Python, while not overwhelming you with too much information. Also, the outputs of ALL the examples are provided immediately so you do not have to wait till you have access to your computer to test the examples. Even if you have never coded before, this is the perfect guide because it breaks down complex concepts into simple steps and in a concise and simple way that fits well with beginners. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them, and the most important real-world applications. Would you like to know more?Scroll Up and Click the BUY NOW Button to Get Your Copy!

📒Python For Data Science ✍ Cooper Turner

Python For Data Science Book PDF
✏Book Title : Python for Data Science
✏Author : Cooper Turner
✏Publisher :
✏Release Date : 2020-04-16
✏Pages : 158
✏ISBN : 9798637765867
✏Available Language : English, Spanish, And French

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✏Python for Data Science Book Summary : MAKE A HUGE STEP IN TODAYS WORLD OF SCIENCE AND TECHNOLOGY! How involved are you in today's world of business and technology? Do you know how powerful it can be to understand and use data analysis in your professional and personal life? Would you like to master one of the world's most widely used programming languages? If you answered "Yes" to at least one of these questions, then keep reading... There are a lot of people out there who think that programming is not for everyone, and they consider it as a very difficult and complicated profession. This concept of "If I don't understand it, I don't need it" causes way more harm than good and holds you away from achieving your goals and fulfilling your dreams. Python Programing Language is one of the most popular and widely used programming languages in the world. And I am not talking about the world of technology, I am talking about the business you are in - food, construction, e-commerce, health, clothing, programming, or any other. How does it work? After more than 2 years of in-depth research and analysis, I decided to create a guide that would help you to understand the most practical methods of Python Programming and Data Analysis and how it can be used to benefit your life. Take a look at only a few things you will get out of this book: What is Data Science, and how to use it? Master the Basics Of Data Science (foundation) A practical guide on Instaling and Working with Python on different Operation Systems A complete Python Set-Up for Data Analysis Data Visualization Methods and strategies How to use Python Data Analysis in your business? Python in Artificial Intelligence and Machine Learning Nr.1 REASON why you should learn and understand Python Programming Much much more... Why this book over other Python Programming guides? Unlike most of the Programming Books out there, especially the ones for beginners, this book is packed with a lot of practical information and strategies on how to start and use the knowledge you are going to get straight after you finish it. This book is complete, but no matter how complete and practical it is, if you want to make it work, you have to take action and start using it. So don't wait, scroll up, click on "Buy Now" and start learning!

📒Python Coding ✍ Eric Wall

Python Coding Book PDF
✏Book Title : Python Coding
✏Author : Eric Wall
✏Publisher : Aicem Limited
✏Release Date : 2020-10-07
✏Pages : 134
✏ISBN : 1914016289
✏Available Language : English, Spanish, And French

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✏Python Coding Book Summary : Are you interested in software development? Are you getting attracted to learning what artificial intelligence is? Do you like to master Python coding? If that's the case, this book, Python Coding: Learn to code Fast Python for data analysis and machine learning. Advanced methods to learn how to create regulations. Practical programming strategies for beginners.is the answer to your concerns! You will find a plethora of languages you could work when we talk about coding. However, none are going to offer you the advantages you'll get with Python coding. The language is extraordinarily sought-after and utilized so often. Did you know a few operating systems, which have some version of Python seen on them for you to use? That could make it simpler to learn some of the coding done that you'd wish and will guarantee you'll receive the best advantages out of it in no time. Keep in mind that the Python language isn't just challenging to read. Inside this book, you will realize that it's a simple job to read some of the various parts of the language. That's especially true even if you're a beginner and haven't been able to work with the language ever. The best part here is that you'll still be able to check some of the systems and see that you understand the details quite well. Here's a preview of what you'll find in this book: - How To Install Python On Windows - Inheritances In Python - Python-Specific Definitions - How To Work With Loops - Analysis Using Panda - Python Machine Learning - Algorithms - Python Classes - Data Files - How To Read Errors And Troubleshooting Your Code - Data Analysis - Mistakes To Avoid With Code - And So Much More! This book is intended for beginners, students, and even professionals who wish to understand how to code and use it to solve challenging real-life concerns. What are you waiting for? Scroll this page and click BUY NOW to get started!

Hands On Data Science And Python Machine Learning Book PDF
✏Book Title : Hands On Data Science and Python Machine Learning
✏Author : Frank Kane
✏Publisher : Packt Publishing Ltd
✏Release Date : 2017-07-31
✏Pages : 420
✏ISBN : 9781787280229
✏Available Language : English, Spanish, And French

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✏Hands On Data Science and Python Machine Learning Book Summary : This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book Take your first steps in the world of data science by understanding the tools and techniques of data analysis Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book. What You Will Learn Learn how to clean your data and ready it for analysis Implement the popular clustering and regression methods in Python Train efficient machine learning models using decision trees and random forests Visualize the results of your analysis using Python's Matplotlib library Use Apache Spark's MLlib package to perform machine learning on large datasets In Detail Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis. Style and approach This comprehensive book is a perfect blend of theory and hands-on code examples in Python which can be used for your reference at any time.

Modeling Techniques In Predictive Analytics With Python And R Book PDF
✏Book Title : Modeling Techniques in Predictive Analytics with Python and R
✏Author : Thomas W. Miller
✏Publisher : FT Press
✏Release Date : 2014-09-29
✏Pages : 448
✏ISBN : 9780133892147
✏Available Language : English, Spanish, And French

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✏Modeling Techniques in Predictive Analytics with Python and R Book Summary : Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Data Analytics For Data Science Big Data Machine Learning Book PDF
✏Book Title : Data Analytics for Data Science Big Data Machine Learning
✏Author : B. Charles Henry
✏Publisher : Createspace Independent Publishing Platform
✏Release Date : 2017-05-16
✏Pages : 196
✏ISBN : 154671605X
✏Available Language : English, Spanish, And French

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✏Data Analytics for Data Science Big Data Machine Learning Book Summary : The contents and practical lab exercises in this text are substantial supplementary materials geared toward Data Analysts, Data Scientists, Business Analysts, and Business Intelligence Practitioners, and for the following certification preparation: Certified Data Professional Certified Business Intelligence Professional Certified Big Data Professional Certified Data Scientist Certified Data Governance Professional