transparentML

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)