mfrdixon/ML_Finance_Codes — reverse-engineered prompt

Build me a Jupyter Notebook project that works as a companion code repo for a Machine Learning in Finance textbook.

I want it organized by chapters, with notebooks for probabilistic modeling, Gaussian processes, neural networks, interpretability, sequence modeling, advanced neural nets, reinforcement learning, finance apps of reinforcement learning, and inverse reinforcement learning. Include a shared data folder and resources folder, plus clear setup instructions so someone can create the right Python environment and run the notebooks on Mac, Windows, Linux, or Google Colab.

The goal is that a student can clone the project, follow the setup guide, open a chapter, and run the examples without guessing what to do. Add short README notes inside each chapter explaining what the notebooks cover. Keep the code educational and readable, not production heavy. Include an environment file, a Windows environment file if needed, a Colab setup notebook, and a simple MIT license notice.