Machine Learning And Data Science In The Power Generation Industry

Machine Learning And Data Science In The Power Generation Industry Book PDF
✏Book Title : Machine Learning and Data Science in the Power Generation Industry
✏Author : Patrick Bangert
✏Publisher : Elsevier
✏Release Date : 2021-03-15
✏Pages : 316
✏ISBN : 0128197420
✏Available Language : English, Spanish, And French

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✏Machine Learning and Data Science in the Power Generation Industry Book Summary : Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study-driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting. Provides best practices on how to design and setup ML projects in power systems, including all nontechnological aspects necessary to be successful Explores implementation pathways, explaining key ML algorithms and approaches as well as the choices that must be made, how to make them, what outcomes may be expected, and how data must be prepared for them Determines the specific data needs for the collection, processing, and operationalization of data within machine learning algorithms for power systems Includes numerous supporting real-world case studies, providing practical guidance on best practices and potential pitfalls

Machine Learning And Data Science In The Oil And Gas Industry Book PDF
✏Book Title : Machine Learning and Data Science in the Oil and Gas Industry
✏Author : Patrick Bangert
✏Publisher : Gulf Professional Publishing
✏Release Date : 2021-03-15
✏Pages : 300
✏ISBN : 0128207140
✏Available Language : English, Spanish, And French

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✏Machine Learning and Data Science in the Oil and Gas Industry Book Summary : Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful Gain practical understanding of machine learning used in oil and gas operations through contributed case studies Learn change management skills that will help gain confidence in pursuing the technology Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)

📒Applying Data Science ✍ Arthur K. Kordon

Applying Data Science Book PDF
✏Book Title : Applying Data Science
✏Author : Arthur K. Kordon
✏Publisher : Springer Nature
✏Release Date :
✏Pages :
✏ISBN : 9783030363758
✏Available Language : English, Spanish, And French

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✏Applying Data Science Book Summary :

Iot Machine Learning Applications In Telecom Energy And Agriculture Book PDF
✏Book Title : IoT Machine Learning Applications in Telecom Energy and Agriculture
✏Author : Puneet Mathur
✏Publisher : Apress
✏Release Date : 2020-05-09
✏Pages : 278
✏ISBN : 9781484255490
✏Available Language : English, Spanish, And French

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✏IoT Machine Learning Applications in Telecom Energy and Agriculture Book Summary : Apply machine learning using the Internet of Things (IoT) in the agriculture, telecom, and energy domains with case studies. This book begins by covering how to set up the software and hardware components including the various sensors to implement the case studies in Python. The case study section starts with an examination of call drop with IoT in the telecoms industry, followed by a case study on energy audit and predictive maintenance for an industrial machine, and finally covers techniques to predict cash crop failure in agribusiness. The last section covers pitfalls to avoid while implementing machine learning and IoT in these domains. After reading this book, you will know how IoT and machine learning are used in the example domains and have practical case studies to use and extend. You will be able to create enterprise-scale applications using Raspberry Pi 3 B+ and Arduino Mega 2560 with Python. What You Will Learn Implement machine learning with IoT and solve problems in the telecom, agriculture, and energy sectors with Python Set up and use industrial-grade IoT products, such as Modbus RS485 protocol devices, in practical scenarios Develop solutions for commercial-grade IoT or IIoT projects Implement case studies in machine learning with IoT from scratch Who This Book Is For Raspberry Pi and Arduino enthusiasts and data science and machine learning professionals.

Data Science For Wind Energy Book PDF
✏Book Title : Data Science for Wind Energy
✏Author : Yu Ding
✏Publisher : CRC Press
✏Release Date : 2019-06-04
✏Pages : 400
✏ISBN : 9780429956515
✏Available Language : English, Spanish, And French

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✏Data Science for Wind Energy Book Summary : Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author’s book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights

Big Data Application In Power Systems Book PDF
✏Book Title : Big Data Application in Power Systems
✏Author : Reza Arghandeh
✏Publisher : Elsevier
✏Release Date : 2017-11-27
✏Pages : 480
✏ISBN : 9780128119693
✏Available Language : English, Spanish, And French

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✏Big Data Application in Power Systems Book Summary : Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement data in electricity transmission and distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data. The book chapters discuss challenges, opportunities, success stories and pathways for utilizing big data value in smart grids. Provides expert analysis of the latest developments by global authorities Contains detailed references for further reading and extended research Provides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformatics Focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data

Data Science And Analytics Book PDF
✏Book Title : Data Science and Analytics
✏Author : Usha Batra
✏Publisher : Springer Nature
✏Release Date : 2020-05-27
✏Pages : 435
✏ISBN : 9789811558276
✏Available Language : English, Spanish, And French

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✏Data Science and Analytics Book Summary : This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics.

Handbook Of Research On Smart Technology Models For Business And Industry Book PDF
✏Book Title : Handbook of Research on Smart Technology Models for Business and Industry
✏Author : Thomas, J. Joshua
✏Publisher : IGI Global
✏Release Date : 2020-06-19
✏Pages : 491
✏ISBN : 9781799836469
✏Available Language : English, Spanish, And French

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✏Handbook of Research on Smart Technology Models for Business and Industry Book Summary : Advances in machine learning techniques and ever-increasing computing power has helped create a new generation of hardware and software technologies with practical applications for nearly every industry. As the progress has, in turn, excited the interest of venture investors, technology firms, and a growing number of clients, implementing intelligent automation in both physical and information systems has become a must in business. Handbook of Research on Smart Technology Models for Business and Industry is an essential reference source that discusses relevant abstract frameworks and the latest experimental research findings in theory, mathematical models, software applications, and prototypes in the area of smart technologies. Featuring research on topics such as digital security, renewable energy, and intelligence management, this book is ideally designed for machine learning specialists, industrial experts, data scientists, researchers, academicians, students, and business professionals seeking coverage on current smart technology models.

Deep Learning Techniques And Optimization Strategies In Big Data Analytics Book PDF
✏Book Title : Deep Learning Techniques and Optimization Strategies in Big Data Analytics
✏Author : Thomas, J. Joshua
✏Publisher : IGI Global
✏Release Date : 2019-11-29
✏Pages : 355
✏ISBN : 9781799811947
✏Available Language : English, Spanish, And French

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✏Deep Learning Techniques and Optimization Strategies in Big Data Analytics Book Summary : Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.

Data Analytics In The Era Of The Industrial Internet Of Things Book PDF
✏Book Title : Data Analytics in the Era of the Industrial Internet of Things
✏Author : Aldo Dagnino
✏Publisher : Springer
✏Release Date : 2021-04-11
✏Pages : 240
✏ISBN : 3030631389
✏Available Language : English, Spanish, And French

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✏Data Analytics in the Era of the Industrial Internet of Things Book Summary : This book presents the characteristics and benefits industrial organizations can reap from the Industrial Internet of Things (IIoT). These characteristics and benefits include enhanced competitiveness, increased proactive decision-making, improved creativity and innovation, augmented job creation, heightened agility to respond to continuously changing challenges, and intensified data-driven decision making. In a straightforward fashion, the book also helps readers understand complex concepts that are core to IIoT enterprises, such as Big Data, analytic architecture platforms, machine learning (ML) and data science algorithms, and the power of visualization to enrich the domains experts’ decision making. The book also guides the reader on how to think about ways to define new business paradigms that the IIoT facilitates, as well how to increase the probability of success in managing analytic projects that are the core engine of decision-making in the IIoT enterprise. The book starts by defining an IIoT enterprise and the framework used to efficiently operate. A description of the concepts of industrial analytics, which is a major engine for decision making in the IIoT enterprise, is provided. It then discusses how data and machine learning (ML) play an important role in increasing the competitiveness of industrial enterprises that operate using the IIoT technology and business concepts. Real world examples of data driven IIoT enterprises and various business models are presented and a discussion on how the use of ML and data science help address complex decision-making problems and generate new job opportunities. The book presents in an easy-to-understand manner how ML algorithms work and operate on data generated in the IIoT enterprise. Useful for any industry professional interested in advanced industrial software applications, including business managers and professionals interested in how data analytics can help industries and to develop innovative business solutions, as well as data and computer scientists who wish to bridge the analytics and computer science fields with the industrial world, and project managers interested in managing advanced analytic projects.

📒Predictive Analytics ✍ Dursun Delen

Predictive Analytics Book PDF
✏Book Title : Predictive Analytics
✏Author : Dursun Delen
✏Publisher : FT Press Analytics
✏Release Date : 2020-10-30
✏Pages : 350
✏ISBN : 0136738516
✏Available Language : English, Spanish, And French

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✏Predictive Analytics Book Summary : In Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for students. Using predictive analytics techniques, students can uncover hidden patterns and correlations in their data, and leverage this insight to improve a wide range of business decisions. Delen's holistic approach covers all this, and more: Data mining processes, methods, and techniques The role and management of data Predictive analytics tools and metrics Techniques for text and web mining, and for sentiment analysis Integration with cutting-edge Big Data approaches Throughout, Delen promotes understanding by presenting numerous conceptual illustrations, motivational success stories, failed projects that teach important lessons, and simple, hands-on tutorials that set this guide apart from competitors.

Data Science And Intelligent Applications Book PDF
✏Book Title : Data Science and Intelligent Applications
✏Author : Ketan Kotecha
✏Publisher : Springer Nature
✏Release Date : 2020-06-17
✏Pages : 576
✏ISBN : 9789811544743
✏Available Language : English, Spanish, And French

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✏Data Science and Intelligent Applications Book Summary : This book includes selected papers from the International Conference on Data Science and Intelligent Applications (ICDSIA 2020), hosted by Gandhinagar Institute of Technology (GIT), Gujarat, India, on January 24–25, 2020. The proceedings present original and high-quality contributions on theory and practice concerning emerging technologies in the areas of data science and intelligent applications. The conference provides a forum for researchers from academia and industry to present and share their ideas, views and results, while also helping them approach the challenges of technological advancements from different viewpoints. The contributions cover a broad range of topics, including: collective intelligence, intelligent systems, IoT, fuzzy systems, Bayesian networks, ant colony optimization, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, speech processing, machine learning and deep learning, and intelligent applications and systems. Helping strengthen the links between academia and industry, the book offers a valuable resource for instructors, students, industry practitioners, engineers, managers, researchers, and scientists alike.

📒Big Data Big Analytics ✍ Michael Minelli

Big Data Big Analytics Book PDF
✏Book Title : Big Data Big Analytics
✏Author : Michael Minelli
✏Publisher : John Wiley & Sons
✏Release Date : 2012-12-27
✏Pages : 224
✏ISBN : 9781118239155
✏Available Language : English, Spanish, And French

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✏Big Data Big Analytics Book Summary : Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

Machine Learning With Tensorflow 1 X Book PDF
✏Book Title : Machine Learning with TensorFlow 1 x
✏Author : Quan Hua
✏Publisher : Packt Publishing Ltd
✏Release Date : 2017-11-21
✏Pages : 304
✏ISBN : 9781786461988
✏Available Language : English, Spanish, And French

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✏Machine Learning with TensorFlow 1 x Book Summary : Tackle common commercial machine learning problems with Google's TensorFlow 1.x library and build deployable solutions. About This Book Enter the new era of second-generation machine learning with Python with this practical and insightful guide Set up TensorFlow 1.x for actual industrial use, including high-performance setup aspects such as multi-GPU support Create pipelines for training and using applying classifiers using raw real-world data Who This Book Is For This book is for data scientists and researchers who are looking to either migrate from an existing machine learning library or jump into a machine learning platform headfirst. The book is also for software developers who wish to learn deep learning by example. Particular focus is placed on solving commercial deep learning problems from several industries using TensorFlow's unique features. No commercial domain knowledge is required, but familiarity with Python and matrix math is expected. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build deep neural networks using TensorFlow 1.x Cover key tasks such as clustering, sentiment analysis, and regression analysis using TensorFlow 1.x Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Learn how to use multiple GPUs for faster training using AWS In Detail Google's TensorFlow is a game changer in the world of machine learning. It has made machine learning faster, simpler, and more accessible than ever before. This book will teach you how to easily get started with machine learning using the power of Python and TensorFlow 1.x. Firstly, you'll cover the basic installation procedure and explore the capabilities of TensorFlow 1.x. This is followed by training and running the first classifier, and coverage of the unique features of the library including data flow graphs, training, and the visualization of performance with TensorBoard—all within an example-rich context using problems from multiple industries. You'll be able to further explore text and image analysis, and be introduced to CNN models and their setup in TensorFlow 1.x. Next, you'll implement a complete real-life production system from training to serving a deep learning model. As you advance you'll learn about Amazon Web Services (AWS) and create a deep neural network to solve a video action recognition problem. Lastly, you'll convert the Caffe model to TensorFlow and be introduced to the high-level TensorFlow library, TensorFlow-Slim. By the end of this book, you will be geared up to take on any challenges of implementing TensorFlow 1.x in your machine learning environment. Style and approach This comprehensive guide will enable you to understand the latest advances in machine learning and will empower you to implement this knowledge in your machine learning environment.

Ai And Big Data S Potential For Disruptive Innovation Book PDF
✏Book Title : AI and Big Data s Potential for Disruptive Innovation
✏Author : Strydom, Moses
✏Publisher : IGI Global
✏Release Date : 2019-09-27
✏Pages : 405
✏ISBN : 9781522596899
✏Available Language : English, Spanish, And French

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✏AI and Big Data s Potential for Disruptive Innovation Book Summary : Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.

Enterprise Artificial Intelligence Transformation Book PDF
✏Book Title : Enterprise Artificial Intelligence Transformation
✏Author : Rashed Haq
✏Publisher : John Wiley & Sons
✏Release Date : 2020-06-23
✏Pages : 368
✏ISBN : 9781119665939
✏Available Language : English, Spanish, And French

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✏Enterprise Artificial Intelligence Transformation Book Summary : Enterprise Artificial Intelligence Transformation AI is everywhere. From doctor's offices to cars and even refrigerators, AI technology is quickly infiltrating our daily lives. AI has the ability to transform simple tasks into technological feats at a human level. This will change the world, plain and simple. That's why AI mastery is such a sought-after skill for tech professionals. Author Rashed Haq is a subject matter expert on AI, having developed AI and data science strategies, platforms, and applications for Publicis Sapient's clients for over 10 years. He shares that expertise in the new book, Enterprise Artificial Intelligence Transformation. The first of its kind, this book grants technology leaders the insight to create and scale their AI capabilities and bring their companies into the new generation of technology. As AI continues to grow into a necessary feature for many businesses, more and more leaders are interested in harnessing the technology within their own organizations. In this new book, leaders will learn to master AI fundamentals, grow their career opportunities, and gain confidence in machine learning. Enterprise Artificial Intelligence Transformation covers a wide range of topics, including: Real-world AI use cases and examples Machine learning, deep learning, and slimantic modeling Risk management of AI models AI strategies for development and expansion AI Center of Excellence creating and management If you're an industry, business, or technology professional that wants to attain the skills needed to grow your machine learning capabilities and effectively scale the work you're already doing, you'll find what you need in Enterprise Artificial Intelligence Transformation.

The 2020 International Conference On Machine Learning And Big Data Analytics For Iot Security And Privacy Book PDF
✏Book Title : The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy
✏Author : John MacIntyre
✏Publisher : Springer Nature
✏Release Date :
✏Pages :
✏ISBN : 9783030627430
✏Available Language : English, Spanish, And French

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✏The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy Book Summary :

Industrial Applications Of Machine Learning Book PDF
✏Book Title : Industrial Applications of Machine Learning
✏Author : Pedro Larrañaga
✏Publisher : CRC Press
✏Release Date : 2018-12-12
✏Pages : 336
✏ISBN : 9781351128360
✏Available Language : English, Spanish, And French

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✏Industrial Applications of Machine Learning Book Summary : Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka

Information Technology Applications In Industry Iii Book PDF
✏Book Title : Information Technology Applications in Industry III
✏Author : Su Fen Yang
✏Publisher : Trans Tech Publications Ltd
✏Release Date : 2014-09-12
✏Pages : 1546
✏ISBN : 9783038266235
✏Available Language : English, Spanish, And French

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✏Information Technology Applications in Industry III Book Summary : Collection of selected, peer reviewed papers from the 2014 3rd International Conference on Information Technology and Management Innovation (ICITMI 2014), July 19-20, 2014, Shenzhen, China. The 294 papers are grouped as follows: Chapter 1: Information Technology, Artificial Intelligence, Algorithms and Computation Methods, Chapter 2: Mathematical Methods and Information Technologies in Power and Electronics Engineering, Chapter 3: Sound, Image, Signal and Video Processing and Technologies, Chapter 4: Sensors, Testing, Detection, Measurement and Monitoring Technologies, Chapter 5: Control and Automation Technology, Modeling and Simulation, Chapter 6: Communications Technology, Chapter 7: Computer Network and Information Security, Chapter 8: Database Systems and Software Development, Chapter 9: E-Commerce, E-Government, Internet Technologies, Chapter 10: Management and Decision Support Systems, Chapter 11: Information Technologies in University and Education

Machine Learning In The Oil And Gas Industry Book PDF
✏Book Title : Machine Learning in the Oil and Gas Industry
✏Author : Yogendra Narayan Pandey
✏Publisher : Apress
✏Release Date : 2020-11-03
✏Pages : 300
✏ISBN : 1484260937
✏Available Language : English, Spanish, And French

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✏Machine Learning in the Oil and Gas Industry Book Summary : Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering. Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry. What You Will Learn Understanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industry Get the basic concepts of computer programming and machine and deep learning required for implementing the algorithms used Study interesting industry problems that are good candidates for being solved by machine and deep learning Discover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is For Professionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.

Big Data And Networks Technologies Book PDF
✏Book Title : Big Data and Networks Technologies
✏Author : Yousef Farhaoui
✏Publisher : Springer
✏Release Date : 2019-07-17
✏Pages : 372
✏ISBN : 9783030236724
✏Available Language : English, Spanish, And French

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✏Big Data and Networks Technologies Book Summary : This book reviews the state of the art in big data analysis and networks technologies. It addresses a range of issues that pertain to: signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart cities, networks technologies, etc. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. In turn, data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and the social sciences. All papers presented here are the product of extensive field research involving applications and techniques related to data analysis in general, and to big data and networks technologies in particular. Given its scope, the book will appeal to advanced undergraduate and graduate students, postdoctoral researchers, lecturers and industrial researchers, as well general readers interested in big data analysis and networks technologies.

Internet Of Things And Big Data Analytics Toward Next Generation Intelligence Book PDF
✏Book Title : Internet of Things and Big Data Analytics Toward Next Generation Intelligence
✏Author : Nilanjan Dey
✏Publisher : Springer
✏Release Date : 2017-08-14
✏Pages : 549
✏ISBN : 9783319604350
✏Available Language : English, Spanish, And French

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✏Internet of Things and Big Data Analytics Toward Next Generation Intelligence Book Summary : This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.

Big Data In Engineering Applications Book PDF
✏Book Title : Big Data in Engineering Applications
✏Author : Sanjiban Sekhar Roy
✏Publisher : Springer
✏Release Date : 2018-05-02
✏Pages : 384
✏ISBN : 9789811084768
✏Available Language : English, Spanish, And French

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✏Big Data in Engineering Applications Book Summary : This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.

Sql For Data Analytics Book PDF
✏Book Title : SQL for Data Analytics
✏Author : Upom Malik
✏Publisher : Packt Publishing Ltd
✏Release Date : 2019-08-23
✏Pages : 386
✏ISBN : 9781789803846
✏Available Language : English, Spanish, And French

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✏SQL for Data Analytics Book Summary : Take your first steps to become a fully qualified data analyst by learning how to explore large relational datasets. Key Features Explore a variety of statistical techniques to analyze your data Integrate your SQL pipelines with other analytics technologies Perform advanced analytics such as geospatial and text analysis Book Description Understanding and finding patterns in data has become one of the most important ways to improve business decisions. If you know the basics of SQL, but don’t know how to use it to gain business insights from data, this book is for you. SQL for Data Analytics covers everything you need progress from simply knowing basic SQL to telling stories and identifying trends in data. You’ll be able to start exploring your data by identifying patterns and unlocking deeper insights. You’ll also gain experience working with different types of data in SQL, including time-series, geospatial, and text data. Finally, you’ll understand how to become productive with SQL with the help of profiling and automation to gain insights faster. By the end of the book, you’ll able to use SQL in everyday business scenarios efficiently and look at data with the critical eye of analytics professional. What you will learn Use SQL to summarize and identify patterns in data Apply special SQL clauses and functions to generate descriptive statistics Use SQL queries and subqueries to prepare data for analysis Perform advanced statistical calculations using the window function Analyze special data types in SQL, including geospatial data and time data Import and export data using a text file and PostgreSQL Debug queries that won't run Optimize queries to improve their performance for faster results Who this book is for If you’re a database engineer looking to transition into analytics, or a backend engineer who wants to develop a deeper understanding of production data, you will find this book useful. This book is also ideal for data scientists or business analysts who want to improve their data analytics skills using SQL. Knowledge of basic SQL and database concepts will aid in understanding the concepts covered in this book.

📒The Deep Learning Workshop ✍ Mirza Rahim Baig

The Deep Learning Workshop Book PDF
✏Book Title : The Deep Learning Workshop
✏Author : Mirza Rahim Baig
✏Publisher : Packt Publishing Ltd
✏Release Date : 2020-07-31
✏Pages : 474
✏ISBN : 9781839210563
✏Available Language : English, Spanish, And French

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✏The Deep Learning Workshop Book Summary : Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text Key Features Understand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognition Study the architecture of different neural networks Book Description Are you fascinated by how deep learning powers intelligent applications such as self-driving cars, virtual assistants, facial recognition devices, and chatbots to process data and solve complex problems? Whether you are familiar with machine learning or are new to this domain, The Deep Learning Workshop will make it easy for you to understand deep learning with the help of interesting examples and exercises throughout. The book starts by highlighting the relationship between deep learning, machine learning, and artificial intelligence and helps you get comfortable with the TensorFlow 2.0 programming structure using hands-on exercises. You'll understand neural networks, the structure of a perceptron, and how to use TensorFlow to create and train models. The book will then let you explore the fundamentals of computer vision by performing image recognition exercises with convolutional neural networks (CNNs) using Keras. As you advance, you'll be able to make your model more powerful by implementing text embedding and sequencing the data using popular deep learning solutions. Finally, you'll get to grips with bidirectional recurrent neural networks (RNNs) and build generative adversarial networks (GANs) for image synthesis. By the end of this deep learning book, you'll have learned the skills essential for building deep learning models with TensorFlow and Keras. What you will learn Understand how deep learning, machine learning, and artificial intelligence are different Develop multilayer deep neural networks with TensorFlow Implement deep neural networks for multiclass classification using Keras Train CNN models for image recognition Handle sequence data and use it in conjunction with RNNs Build a GAN to generate high-quality synthesized images Who this book is for If you are interested in machine learning and want to create and train deep learning models using TensorFlow and Keras, this workshop is for you. A solid understanding of Python and its packages, along with basic machine learning concepts, will help you to learn the topics quickly.

Building Machine Learning Pipelines Book PDF
✏Book Title : Building Machine Learning Pipelines
✏Author : Hannes Hapke
✏Publisher : "O'Reilly Media, Inc."
✏Release Date : 2020-07-13
✏Pages : 366
✏ISBN : 9781492053149
✏Available Language : English, Spanish, And French

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✏Building Machine Learning Pipelines Book Summary : Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation and TensorFlow Transform Analyze a model in detail using TensorFlow Model Analysis Examine fairness and bias in your model performance Deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices Learn privacy-preserving machine learning techniques

15th International Conference On Soft Computing Models In Industrial And Environmental Applications Soco 2020  Book PDF
✏Book Title : 15th International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO 2020
✏Author : Álvaro Herrero
✏Publisher : Springer Nature
✏Release Date : 2020-08-28
✏Pages : 876
✏ISBN : 9783030578022
✏Available Language : English, Spanish, And French

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✏15th International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO 2020 Book Summary : This book contains accepted papers presented at SOCO 2020 conference held in the beautiful and historic city of Burgos (Spain), in September 2020. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the SOCO 2020 International Program Committee selected 83 papers which are published in these conference proceedings and represents an acceptance rate of 35%. Due to the COVID-19 outbreak, the SOCO 2020 edition was blended, combining on-site and on-line participation. In this relevant edition a special emphasis was put on the organization of special sessions. Eleven special session were organized related to relevant topics such as: Soft Computing Applications in Precision Agriculture, Manufacturing and Management Systems, Management of Industrial and Environmental Enterprises, Logistics and Transportation Systems, Robotics and Autonomous Vehicles, Computer Vision, Laser-Based Sensing and Measurement and other topics such as Forecasting Industrial Time Series, IoT, Big Data and Cyber Physical Systems, Non-linear Dynamical Systems and Fluid Dynamics, Modeling and Control systems The selection of papers was extremely rigorous in order to maintain the high quality of SOCO conference editions and we would like to thank the members of the Program Committees for their hard work in the reviewing process. This is a crucial process to the creation of a high standard conference and the SOCO conference would not exist without their help.

📒Keras To Kubernetes ✍ Dattaraj Rao

Keras To Kubernetes Book PDF
✏Book Title : Keras to Kubernetes
✏Author : Dattaraj Rao
✏Publisher : Wiley
✏Release Date : 2019-05-07
✏Pages : 400
✏ISBN : 9781119564836
✏Available Language : English, Spanish, And French

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✏Keras to Kubernetes Book Summary : Build a Keras model to scale and deploy on a Kubernetes cluster We have seen an exponential growth in the use of Artificial Intelligence (AI) over last few years. AI is becoming the new electricity and is touching every industry from retail to manufacturing to healthcare to entertainment. Within AI, were seeing a particular growth in Machine Learning (ML) and Deep Learning (DL) applications. ML is all about learning relationships from labeled (Supervised) or unlabeled data (Unsupervised). DL has many layers of learning and can extract patterns from unstructured data like images, video, audio, etc. em style="box-sizing: border-box;"Keras to Kubernetes: The Journey of a Machine Learning Model to Production takes you through real-world examples of building DL models in Keras for recognizing product logos in images and extracting sentiment from text. You will then take that trained model and package it as a web application container before learning how to deploy this model at scale on a Kubernetes cluster. You will understand the different practical steps involved in real-world ML implementations which go beyond the algorithms. • Find hands-on learning examples • Learn to uses Keras and Kubernetes to deploy Machine Learning models • Discover new ways to collect and manage your image and text data with Machine Learning • Reuse examples as-is to deploy your models • Understand the ML model development lifecycle and deployment to production If youre ready to learn about one of the most popular DL frameworks and build production applications with it, youve come to the right place!

Supervised And Unsupervised Learning For Data Science Book PDF
✏Book Title : Supervised and Unsupervised Learning for Data Science
✏Author : Michael W. Berry
✏Publisher : Springer Nature
✏Release Date : 2019-09-04
✏Pages : 187
✏ISBN : 9783030224752
✏Available Language : English, Spanish, And French

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✏Supervised and Unsupervised Learning for Data Science Book Summary : This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a comprehensive reference to the field. The book is organized into eight chapters that cover the following topics: discretization, feature extraction and selection, classification, clustering, topic modeling, graph analysis and applications. Practitioners and graduate students can use the volume as an important reference for their current and future research and faculty will find the volume useful for assignments in presenting current approaches to unsupervised and semi-supervised learning in graduate-level seminar courses. The book is based on selected, expanded papers from the Fourth International Conference on Soft Computing in Data Science (2018). Includes new advances in clustering and classification using semi-supervised and unsupervised learning; Address new challenges arising in feature extraction and selection using semi-supervised and unsupervised learning; Features applications from healthcare, engineering, and text/social media mining that exploit techniques from semi-supervised and unsupervised learning.

Big Data Analytics Systems Algorithms Applications Book PDF
✏Book Title : Big Data Analytics Systems Algorithms Applications
✏Author : C.S.R. Prabhu
✏Publisher : Springer Nature
✏Release Date : 2019-10-14
✏Pages : 412
✏ISBN : 9789811500947
✏Available Language : English, Spanish, And French

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✏Big Data Analytics Systems Algorithms Applications Book Summary : This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.