O'Reilly AI and ML for Coders in Pytorch: A Coder's Guide to Generative AI and Machine Learning

AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence

O'Reilly

Mastering PyTorch: Build powerful neural network architectures using advanced PyTorch 1.x features

Packt Publishing

Hands-On Machine Learning with Scikit-Learn and PyTorch: Concepts, Tools, and Techniques to Build Intelligent Systems

O'Reilly

Deep Learning with PyTorch, Second Edition

Manning

Python, Deep Learning, and LLMs: A Crash Course for Complete Beginners

Artificial Intelligence with Python (Machine Learning: Foundations, Methodologies, and Applications)

Springer

Deep Learning at Scale: At the Intersection of Hardware, Software, and Data

O'Reilly

Deep Learning with Python, Third Edition

Manning

Artificial Intelligence with Python (Machine Learning: Foundations, Methodologies, and Applications)

Springer

Hands-on Machine Learning with Python: Implement Neural Network Solutions with Scikit-learn and PyTorch

Apress

Machine Learning: From the Classics to Deep Networks, Transformers, and Diffusion Models

Practicing Trustworthy Machine Learning: Consistent, Transparent, and Fair AI Pipelines

O'Reilly

Hands-On Artificial Intelligence for Beginners: An introduction to AI concepts, algorithms, and their implementation

Packt Publishing

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

Packt Publishing

Generative AI with Python: The Developer's Guide to Pretrained Llms, Vector Databases, Retrieval-Augmented Generation, and Agentic Systems

Rheinwerk Computing

Time Series Forecasting Using Generative AI: Leveraging AI for Precision Forecasting

Artificial Intelligence for Learning: Using AI and Generative AI to Support Learner Development

Kogan Page

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems

O'Reilly

Principles and Labs for Deep Learning

Academic Press

Springer Explainable and Interpretable Models in Machine Learning

Springer

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

Apress

Machine Learning and Artificial Intelligence: Concepts, Algorithms and Models

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)

Modern Computer Vision with PyTorch: A practical roadmap from deep learning fundamentals to advanced applications and Generative AI

Packt Publishing