aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

A guidance language for controlling large language models.

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

Examples and guides for using the Gemini API

Data and code behind the articles and graphics at FiveThirtyEight

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Bayesian optimization in PyTorch

🔥 Machine Learning Notebooks

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

LeetCode for PyTorch — 65 ML/AI interview problems from real interviews at Google, Meta, Anthropic. Jupyter notebooks, an auto-grader, and an MCP AI tutor.

A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.

Source code for my collection of articles on using pandas.

Bayesian Data Analysis demos for Python

Easy pipelines for pandas DataFrames.

A template for small scientific python projects

Pelican plugin for blogging with Jupyter/IPython Notebooks

🎲 Notes explaining Dirichlet Processes, HDPs, and Latent Dirichlet Allocation

A Multipurpose Library for Synthetic Time Series Generation in Python

Implementation of various topic models

An implementation of some of the tools used by the winner of the box plots competition using scikit-learn.

Using Project Jupyter for data science.

A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.

K-Means clustering - constrained with minimum and maximum cluster size. Documentation: https://joshlk.github.io/k-means-constrained

Source code to reproduce experiments from the article Practitioner’s Guide to Statistical Tests

Playground for various AI projects and demos

Code for the paper: "Large Language Models as Corporate Lobbyists" (2023).

A repository of machine learning codes written for re-usability

A concise syntax to describe and execute routine data analysis tasks

Methods, tools, tips, and tricks for anyone interested in getting started doing data science for the social good.

a nose plugin for finding and running IPython notebooks as nose tests