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Chollet, F. (2021). Deep learning with Python (2nd ed.). Manning Publications.
Read Chapter 5: Fundamentals of Machine Learning
Read Chapter 6: The Universal Workflow of Machine Learning

This book is a hands-on, beginner-friendly guide to understanding and building deep learning models using Python and Keras, with real-world examples spanning vision, text, and structured data.

Lapan, M. (2024). Deep reinforcement learning hands-on (3rd ed.). O’Reilly Learning Platform.
Read Chapter 3: Deep Learning with PyTorch
Read Chapter 4: The Cross-Entropy Method
Read Chapter 6: Deep Q-Networks

This book offers a hands-on introduction to deep learning using the Keras library, guiding readers through core concepts, practical applications, and best practices for building and training neural networks.

Johnny Code. (n.d.). Johnny Code [YouTube channel]. YouTube. https://www.youtube.com/@johnnycode

If you're returning to study or building new technical skills, Johnny Code's YouTube channel offers clear, hands-on instruction in Python, machine learning, and reinforcement learning. The content is well-paced, practical, and designed to help you grasp complex topics without needing a technical background.

Kapoor, A., Gulli, A., & Pal, S. (2022). Deep learning with TensorFlow and Keras (3rd ed.). Packt Publishing.

This book is a hands‑on guide that teaches Python developers and data scientists to build and deploy a wide range of deep learning models—from CNNs, RNNs, transformers, GANs, GNNs, and reinforcement learning—using TensorFlow 2.x and Keras, with extensive practical examples for both research and production environments .