Machine Learning Guide for Oil and Gas Using Python

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  • Author : Hoss Belyadi
  • Publisher : Elsevier
  • Pages : 476 pages
  • ISBN : 0128219297
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Machine Learning Guide for Oil and Gas Using Python

Download or Read online Machine Learning Guide for Oil and Gas Using Python full in PDF, ePub and kindle. this book written by Hoss Belyadi and published by Elsevier which was released on 27 April 2021 with total page 476 pages. We cannot guarantee that Machine Learning Guide for Oil and Gas Using Python book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges. Helps readers understand how open-source Python can be utilized in practical oil and gas challenges Covers the most commonly used algorithms for both supervised and unsupervised learning Presents a balanced approach of both theory and practicality while progressing from introductory to advanced analytical techniques

Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python
  • Author : Hoss Belyadi,Alireza Haghighat
  • Publisher : Elsevier
  • Release : 27 April 2021
GET THIS BOOK Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their

Machine Learning in the Oil and Gas Industry

Machine Learning in the Oil and Gas Industry
  • Author : Yogendra Narayan Pandey,Ayush Rastogi,Sribharath Kainkaryam,Srimoyee Bhattacharya,Luigi Saputelli
  • Publisher : Apress
  • Release : 03 November 2020
GET THIS BOOK Machine Learning in the Oil and Gas Industry

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

Machine Learning and Data Science in the Oil and Gas Industry

Machine Learning and Data Science in the Oil and Gas Industry
  • Author : Patrick Bangert
  • Publisher : Elsevier
  • Release : 15 March 2021
GET THIS BOOK Machine Learning and Data Science in the Oil and Gas Industry

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

Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python
  • Author : Hoss Belyadi,Alireza Haghighat
  • Publisher : Gulf Professional Publishing
  • Release : 09 April 2021
GET THIS BOOK Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their

Building Machine Learning Systems Using Python

Building Machine Learning Systems Using Python
  • Author : Dr Deepti Chopra
  • Publisher : BPB Publications
  • Release : 07 May 2021
GET THIS BOOK Building Machine Learning Systems Using Python

Explore Machine Learning Techniques, Different Predictive Models, and its Applications KEY FEATURES ● Extensive coverage of real examples on implementation and working of ML models. ● Includes different strategies used in Machine Learning by leading data scientists. ● Focuses on Machine Learning concepts and their evolution to algorithms. DESCRIPTION This book covers basic concepts of Machine Learning, various learning paradigms, different architectures and algorithms used in these paradigms. You will learn the power of ML models by exploring different predictive modeling techniques such

Python Machine Learning for Beginners

Python Machine Learning for Beginners
  • Author : Ai Publishing
  • Publisher : Unknown
  • Release : 23 October 2020
GET THIS BOOK Python Machine Learning for Beginners

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

Machine Learning for Cybersecurity Cookbook

Machine Learning for Cybersecurity Cookbook
  • Author : Emmanuel Tsukerman
  • Publisher : Packt Publishing Ltd
  • Release : 25 November 2019
GET THIS BOOK Machine Learning for Cybersecurity Cookbook

Learn how to apply modern AI to create powerful cybersecurity solutions for malware, pentesting, social engineering, data privacy, and intrusion detection Key Features Manage data of varying complexity to protect your system using the Python ecosystem Apply ML to pentesting, malware, data privacy, intrusion detection system(IDS) and social engineering Automate your daily workflow by addressing various security challenges using the recipes covered in the book Book Description Organizations today face a major threat in terms of cybersecurity, from malicious

Transactional Machine Learning with Data Streams and AutoML

Transactional Machine Learning with Data Streams and AutoML
  • Author : Sebastian Maurice
  • Publisher : Apress
  • Release : 20 May 2021
GET THIS BOOK Transactional Machine Learning with Data Streams and AutoML

Understand how to apply auto machine learning to data streams and create transactional machine learning (TML) solutions that are frictionless (require minimal to no human intervention) and elastic (machine learning solutions that can scale up or down by controlling the number of data streams, algorithms, and users of the insights). This book will strengthen your knowledge of the inner workings of TML solutions using data streams with auto machine learning integrated with Apache Kafka. Transactional Machine Learning with Data Streams

Machine Learning for Time Series Forecasting with Python

Machine Learning for Time Series Forecasting with Python
  • Author : Francesca Lazzeri
  • Publisher : John Wiley & Sons
  • Release : 15 December 2020
GET THIS BOOK Machine Learning for Time Series Forecasting with Python

Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling. Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine

Math for Programmers

Math for Programmers
  • Author : Paul Orland
  • Publisher : Manning Publications
  • Release : 12 January 2021
GET THIS BOOK Math for Programmers

In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. Summary To score a job in data science, machine learning, computer graphics, and cryptography,

Methods for Petroleum Well Optimization

Methods for Petroleum Well Optimization
  • Author : Rasool Khosravanian,Bernt S. Aadnoy
  • Publisher : Gulf Professional Publishing
  • Release : 24 September 2021
GET THIS BOOK Methods for Petroleum Well Optimization

Drilling and production wells are becoming more digitalized as oil and gas companies continue to implement machine learning and big data solutions to save money on projects while reducing energy and emissions. Up to now there has not been one cohesive resource that bridges the gap between theory and application, showing how to go from computer modeling to practical use. Methods for Petroleum Well Optimization: Automation and Data Solutions gives today’s engineers and researchers real-time data solutions specific to

Machine Learning Solutions

Machine Learning Solutions
  • Author : Jalaj Thanaki
  • Publisher : Packt Publishing Ltd
  • Release : 27 April 2018
GET THIS BOOK Machine Learning Solutions

Practical, hands-on solutions in Python to overcome any problem in Machine Learning Key Features Master the advanced concepts, methodologies, and use cases of machine learning Build ML applications for analytics, NLP and computer vision domains Solve the most common problems in building machine learning models Book Description Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across

Hydraulic Fracturing in Unconventional Reservoirs

Hydraulic Fracturing in Unconventional Reservoirs
  • Author : Hoss Belyadi,Ebrahim Fathi,Fatemeh Belyadi
  • Publisher : Gulf Professional Publishing
  • Release : 24 November 2016
GET THIS BOOK Hydraulic Fracturing in Unconventional Reservoirs

Hydraulic Fracturing in Unconventional Reservoirs: Theories, Operations, and Economic Analysis introduces the basic characteristics and theories surrounding hydraulic fracturing and the main process of fracturing in shale, including the main workflow, the details in case analysis, and the fundamental differences between theory, study, and practical operation. The book takes the complex nature of the hydraulic fracturing in unconventional reservoirs and applies a practical approach that can be useds as a workflow for designing fracture treatments in various shale basins across

IoT Machine Learning Applications in Telecom Energy and Agriculture

IoT Machine Learning Applications in Telecom  Energy  and Agriculture
  • Author : Puneet Mathur
  • Publisher : Apress
  • Release : 09 May 2020
GET THIS BOOK IoT Machine Learning Applications in Telecom Energy and Agriculture

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