tensorflow_cookbook

Why we included this project

The code here accompanies the Packt book 'TensorFlow Machine Learning Cookbook', and it reads as a teaching resource rather than something you would deploy. The chapters group dozens of runnable Jupyter notebooks that move from TensorFlow basics through linear regression, SVMs, nearest-neighbor methods, neural networks, NLP, CNNs, RNNs, and a closing section on taking models to production. Each recipe is self-contained, with the algorithm explained before the code, which suits developers and students who learn by reading and running concrete examples. Because the coverage spans so many classic techniques, it doubles as a structured refresher for anyone revisiting TensorFlow or a place to copy a specific pattern from. Just keep in mind the code targets the older TensorFlow 1.x APIs, so treat it as a conceptual guide rather than a drop-in for modern projects.