Machine learning and data science in the oil and gas industry, Patrick Bangert
Автор: Strang Gilbert Название: Linear Algebra and Learning from Data ISBN: 0692196382 ISBN-13(EAN): 9780692196380 Издательство: Cambridge Academ Рейтинг: Цена: 9978.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.
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.
Автор: Keith R. Holdaway Название: Enhance Oil & Gas Exploration with Data-Driven Geo physical and Petrophysical Models ISBN: 1119215102 ISBN-13(EAN): 9781119215103 Издательство: Wiley Рейтинг: Цена: 8316.00 р. 11880.00-30% Наличие на складе: Есть (1 шт.) Описание: Leverage Big Data analytics methodologies to add value to geophysical and petrophysical exploration data Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models demonstrates a new approach to geophysics and petrophysics data analysis using the latest methods drawn from Big Data.
Автор: Urry Jane Название: Advances in Oil and Gas Industry ISBN: 1632400529 ISBN-13(EAN): 9781632400529 Издательство: Неизвестно Цена: 17694.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
The international petroleum industry has long been known the world over as a "good old boys' club" and nowhere is the oil and gas industry's gender imbalance more apparent than offshore. The untold story, shared in these pages, is about the women who have been among the first to inhabit this world, and whose stories previously have been a missing part of the history of the industry.
"As a CEO, I believe it is imperative for today's generation of young women to realize there is a seat for them in the boards of oil & gas companies as the "gas ceiling" can be broken quicker and easier than before. Reading this book, they will think about these women who have gone before them and broken down those barriers in order to give them new opportunities." -- Maria Mor us Hanssen, CEO, DEA Deutsche Erdoel AG
"My belief is that diversity is key to both creativity and solid long-term business results. Even in a country like Norway, where professional gender diversity is greater than in any other country I have had interactions with, we have an underrepresentation of women in top management positions. I would therefore like to express my appreciation to Rebecca Ponton for keeping this important subject on the agenda by presenting to us positive, impressive and, at the same time, obtainable role models." -- Grethe K. Moen, CEO and President, Petoro AS
"As the industry now is more complex and faces more uncertainty, women will be more important contributors, especially in management and communication. Women could be just what is needed " -- Karen Sund, Founder Sund Energy AS
"Everyone needs role models - and role models that look like you are even better. For women, the oil and gas industry has historically been pretty thin on role models for young women to look up to. Rebecca Ponton has provided an outstanding compilation of role models for all women who aspire to success in one of the most important industries of modern times." -- Dave Payne, Chevron VP Drilling & Completions
Learn more at www.BreakingTheGasCeiling.com From the World Voices Series at Modern History Press www.ModernHistoryPress.com
The international petroleum industry has long been known the world over as a "good old boys' club" and nowhere is the oil and gas industry's gender imbalance more apparent than offshore. The untold story, shared in these pages, is about the women who have been among the first to inhabit this world, and whose stories previously have been a missing part of the history of the industry.
"As a CEO, I believe it is imperative for today's generation of young women to realize there is a seat for them in the boards of oil & gas companies as the "gas ceiling" can be broken quicker and easier than before. Reading this book, they will think about these women who have gone before them and broken down those barriers in order to give them new opportunities." -- Maria Mor us Hanssen, CEO, DEA Deutsche Erdoel AG
"My belief is that diversity is key to both creativity and solid long-term business results. Even in a country like Norway, where professional gender diversity is greater than in any other country I have had interactions with, we have an underrepresentation of women in top management positions. I would therefore like to express my appreciation to Rebecca Ponton for keeping this important subject on the agenda by presenting to us positive, impressive and, at the same time, obtainable role models." -- Grethe K. Moen, CEO and President, Petoro AS
"As the industry now is more complex and faces more uncertainty, women will be more important contributors, especially in management and communication. Women could be just what is needed " -- Karen Sund, Founder Sund Energy AS
"Everyone needs role models - and role models that look like you are even better. For women, the oil and gas industry has historically been pretty thin on role models for young women to look up to. Rebecca Ponton has provided an outstanding compilation of role models for all women who aspire to success in one of the most important industries of modern times." -- Dave Payne, Chevron VP Drilling & Completions
Learn more at www.BreakingTheGasCeiling.com From the World Voices Series at Modern History Press www.ModernHistoryPress.com
Описание: Muso DJ music playlist game, streaming music card game, adult card game for music lovers, students, friends and family, party music game where you`re the DJ, use with any music streaming app.Muso DJ is the music playlist party game you will want to play again and again. Play music you love and score points while others guess the artist, track and category. A music board game; ideal at parties and dinners. Unlike some music games/party games, you don`t need a DJ app for this quiz game with a twist. More than a trivia game for adults, Muso DJ is the ideal music-based card game for dinner guests, friends, families or students - whether at home or on holiday. As a music quiz game, it`s easy to learn: Take it in turns to pick tunes that relate to categories and tell your stories if you want to. Everyone plays at once: You`re always either playing a tune or taking a guess and yes: You all get to be the DJ. Use music-streaming services including Spotify, Apple Music, YouTube, Amazon Music and Deezer to play your favourite tunes. Even if you are not a popular music fan or a fan of quiz games, this DJ game is one of the few music games for adults that everyone from teens to adults can enjoy. A music party game with a difference; guess, chat and play with Muso DJ: The music playlist party game.
Автор: Yogendra Narayan Pandey et al Название: Machine learning in the oil and gas industry ISBN: 1484260937 ISBN-13(EAN): 9781484260937 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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 LearnUnderstanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industryGet the basic concepts of computer programming and machine and deep learning required for implementing the algorithms usedStudy interesting industry problems that are good candidates for being solved by machine and deep learningDiscover 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.
Описание: Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python if you are only comfortable with R.As in the first edition, the authors have kept the fine balance of theory and application of machine learning through various real-world use-cases which gives you a comprehensive collection of topics in machine learning. New chapters in this edition cover time series models and deep learning.What You'll Learn Understand machine learning algorithms using RMaster the process of building machine-learning models Cover the theoretical foundations of machine-learning algorithmsSee industry focused real-world use casesTackle time series modeling in RApply deep learning using Keras and TensorFlow in RWho This Book is ForData scientists, data science professionals, and researchers in academia who want to understand the nuances of machine-learning approaches/algorithms in practice using R.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Raschka, Sebastian Mirjalili, Vahid Название: Python machine learning - ISBN: 1787125939 ISBN-13(EAN): 9781787125933 Издательство: Неизвестно Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This second edition of Python Machine Learning by Sebastian Raschka is for developers and data scientists looking for a practical approach to machine learning and deep learning. In this updated edition, you`ll explore the machine learning process using Python and the latest open source technologies, including scikit-learn and TensorFlow 1.x.
Описание: Machine Learning and Data Science in the Power Generation Industry: Best Practices, Tools, and Case Studies explores current best practices and quantifies the value-add in developing data-oriented computational programs in the energy industry, with a focus on real-world case studies selected from modern practice. The book provides a set of realistic pathways for organizations seeking to develop machine learning methods, with discussion on data selection and curation, as well as organizational implementation in terms of staffing and continuing operationalization. The book articulates a body of case study-driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, emissions credits, and forecasting.
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