Wisconsin Breast Cancer Prediction through Decision Tree along with exploratory diagnostics

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

Uplift modeling and causal inference with machine learning algorithms

An example of using uv in Docker images

Reviewing the performance of Matrix Multiplication in multiple languages

Reactive marmio notebooks about matrix factorization used in solving SVD, PCA, linear systems.

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

Jupyter Notebook used for writing the article "Black-Box models are actually more explainable than a Logistic Regression" published in Towards Data Science: https://towardsdatascience.com/black-box…

The fastai book, published as Jupyter Notebooks

A framework for comprehensive diagnosis and optimization of agents using simulated, realistic synthetic interactions

🟣 Pandas interview questions and answers to help you prepare for your next machine learning and data science interview in 2026.

👑 Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA

skimpy is a light weight tool that provides summary statistics about variables in data frames within the console.

Shapley Interactions and Shapley Values for Machine Learning

Machine learning in Python with scikit-learn MOOC

Typer, build great CLIs. Easy to code. Based on Python type hints.

Book about interpretable machine learning

EvalML is an AutoML library written in python.

Vane is an AI-powered answering engine.

🧬🐍 Generative UI web application built with LangChain Python, AI SDK & Next.js

scikit-learn: machine learning in Python

Fit interpretable models. Explain blackbox machine learning.

An Open Source Machine Learning Framework for Everyone