donnemartin/data-science-ipython-notebooks ? reverse-engineered prompt

I'd like to create a big collection of Python notebooks for learning data science and machine learning. The goal is to build a go-to resource that people can use to study or as a reference guide, so it should be very comprehensive and well-organized.

Please structure the project with a main folder for each major topic. I'm thinking of sections for deep learning (with examples for TensorFlow, Keras, and others), traditional machine learning using scikit-learn, data analysis with pandas and NumPy, and data visualization with matplotlib. It would also be great to have sections on big data concepts like Spark and MapReduce, and maybe some helpful command-line tips and AWS guides.

Each notebook should be a focused tutorial on a specific concept, like how to build a neural network or perform logistic regression. The main README file should be the centerpiece, acting as a detailed index or table of contents that links to every section and notebook.