Description: Machine Learning Guide for Oil and Gas Using Python : A Step-by-step Breakdown With Data, Algorithms, Codes, and Applications, Paperback by Belyadi, Hoss; Haghighat, Alireza, ISBN 0128219297, ISBN-13 9780128219294, Like New Used, Free shipping in the US
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 bookbalances 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
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End Time: 2024-09-26T22:43:43.000Z
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Book Title: Machine Learning Guide for Oil and Gas Using Python : A Step-by-s
Number of Pages: 300 Pages
Publication Name: Machine Learning Guide for Oil and Gas Using Python : A Step-By-Step Breakdown with Data, Algorithms, Codes, and Applications
Language: English
Publisher: Elsevier Science & Technology
Publication Year: 2021
Subject: Mining, Energy, Intelligence (Ai) & Semantics, Power Resources / Fossil Fuels
Type: Textbook
Subject Area: Computers, Technology & Engineering, Science
Item Length: 9 in
Author: Alireza Haghighat, Hoss Belyadi
Item Width: 6 in
Format: Trade Paperback
