Practical-Deep-Learning-Book

Why we included this project

The O'Reilly book 'Practical Deep Learning for Cloud, Mobile, and Edge' by Anirudh Koul, Siddha Ganju, and Meher Kasam ships with this companion repository, and the code is organized so it works as a learning path rather than a single deployable tool. Each chapter comes with runnable notebooks and scripts that walk you through real tasks: image classification in a few lines of Keras, transfer learning, building a reverse image search engine from embeddings, and moving models onto Raspberry Pi, Jetson Nano, and Google Coral. Because the material is tied to a published text and arranged by chapter, it reads well as a self-paced curriculum, and it doubles as a reference when you need a concrete example of something like TensorFlow Lite conversion or Core ML integration. The Keras project also lists it as a learning resource, which is a useful signal for anyone weighing it against scattered blog tutorials.