467: High-Impact Data Science Made Easy

Deep Learning Illustrated is a comprehensive guide to deep learning, offering a unique visual and interactive approach. It explains deep learning techniques through straightforward analogies, vivid illustrations, and hands-on Python code in Jupyter notebooks. The book covers essential theory, including artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), and deep reinforcement learning. It also focuses on practical applications such as machine vision, natural language processing, image generation, and game-playing algorithms, using libraries like Keras, TensorFlow, and PyTorch.

In 'The Code Breaker,' Sally Pierson Dillon tells the story of Donnie, a young boy who, after breaking his leg, discovers intriguing secrets from his family's past through the sounds he hears in the old house. The book explores themes of family history, personal growth, and the importance of understanding one's roots.

This book teaches how to use Python for automating Linux systems, developing software with containers, and leveraging DevOps tools like Docker, Kubernetes, and Terraform. It covers topics from Python foundations to machine learning operations and data engineering.