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An Introduction to Transparent Machine Learning
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and beyond.
PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics
[HELP REQUESTED] Generalized Additive Models in Python
Free and open source code of the https://tournesol.app platform. Meet the community on Discord https://discord.gg/WvcSG55Bf3
Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting
???♂? Interpreting Convolutional Neural Network (CNN) Results.
Solutions to exercises from Introduction to Statistical Learning (ISLR 1st Edition)