Emtiaz-10/handson-ml3 — reverse-engineered prompt

Build me a friendly learning notebook project for machine learning in Python, like a hands on course someone can run locally or open online. It should guide a beginner through the main topics step by step, starting with the machine learning landscape and an end to end project, then classification, linear models, support vector machines, decision trees, random forests, dimensionality reduction, unsupervised learning, neural networks, computer vision, sequence models, NLP, autoencoders, GANs, diffusion models, reinforcement learning, and deploying at scale.

Please set it up as Jupyter notebooks with clear explanations, runnable example code, exercises or practice sections, and helpful visuals where useful. Include setup files so someone can install the environment with conda, run it in Jupyter, or use Docker if they prefer. Also add basic install instructions, a project index notebook, and a short checklist for doing an ML project.

Use Scikit Learn, Keras, and TensorFlow where appropriate. Look up current docs online if you need to.