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Machine Learning Guide for Oil and Gas Using Python Belyadi Haghighat Paperback

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Machine Learning Guide for Oil and Gas Using Python

A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications

Helps readers learn how Python can solve practical applications of machine learning in the oil and gas industry

Hoss Belyadi (Author), Alireza Haghighat (Author)

9780128219294

Paperback / softback, published 13 April 2021

476 pages

22.9 x 15.2 x 3 cm, 0.77 kg

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]

Machine Learning Guide for Oil and Gas Using Python Belyadi Haghighat Paperback

Machine Learning Guide for Oil and Gas Using Python

A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications

Helps readers learn how Python can solve practical applications of machine learning in the oil and gas industry

Hoss Belyadi (Author), Alireza Haghighat (Author)

9780128219294

Paperback / softback, published 13 April 2021

476 pages

22.9 x 15.2 x 3 cm, 0.77 kg

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]

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