Gulf Professional Publishing Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications

Practical Machine Learning for Data Analysis Using Python

Academic Press

Machine Learning for Subsurface Characterization

Gulf Professional Publishing

Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis

CRC Press

Practical Machine Learning with Python: A Problem-Solver's Guide to Building Real-World Intelligent Systems

Apress

Machine Learning with Python: Theory and Implementation

Introduction to Machine Learning with Python: A Guide for Data Scientists

O'Reilly

Machine Learning for Decision Sciences with Case Studies in Python

Unconventional Shale Gas Development: Lessons Learned - Gulf Publishing

Gulf Professional Publishing

Advances in Subsurface Data Analytics: Traditional and Physics-Based Machine Learning

Elsevier

Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python

Packt Publishing

Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment)

Springer

A Greater Foundation for Machine Learning Engineering: The Hallmarks of the Great Beyond in Pytorch, R, Tensorflow, and Python

Authorhouse

Machine Learning for Engineers: Using data to solve problems for physical systems

Springer

Data-Driven Reservoir Modeling

Society of Petroleum Engineers

Mastering Machine Learning with Python in Six Steps: A Practical Implementation Guide to Predictive Data Analytics Using Python

Apress

Python Machine Learning Case Studies: Five Case Studies for the Data Scientist

Apress

Machine Learning for Science and Engineering: Volume I: Fundamentals (Course Notes)

Understanding Deep Learning: Building Machine Learning Systems with PyTorch and TensorFlow: From Neural Networks (CNN, DNN, GNN, RNN, ANN, LSTM, GAN) to Natural Language Processing (NLP)

Understanding Deep Learning: Building Machine Learning Systems with PyTorch and TensorFlow: From Neural Networks (CNN, DNN, GNN, RNN, ANN, LSTM, GAN) to Natural Language Processing (NLP)

Python Applications in Chemical Engineering:: Process Simulation, Optimization, and Data Analysis

Machine Learning Foundations: Volume 1: Supervised Learning

Addison Wesley

Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment)

Springer

Wiley AI and Data Analytics for Energy Exploration and Production

John Wiley & Sons Inc

scikit-learn : Machine Learning Simplified: Implement scikit-learn into every step of the data science pipeline

Packt Publishing