ageron/handson-ml ? reverse-engineered prompt

Build me a Jupyter notebook project that teaches machine learning step by step, like a companion to a beginner friendly book.

I want an index notebook that lets me jump into different lessons, starting with the basics and moving through classification, linear models, support vector machines, decision trees, ensembles, dimensionality reduction, TensorFlow, neural networks, convolutional and recurrent networks, autoencoders, and reinforcement learning. It should also include a few extra notebooks for math, NumPy, pandas, Matplotlib, and gradient descent so the examples are easier to follow.

Make it easy to run locally in a clean Python environment, and also simple to open online if possible. Include any setup needed for data, dependencies, and a smooth notebook experience. If you need to look up current docs online while building it, go ahead. The goal is for someone to open the notebooks and learn by running the examples themselves.