Tutorial on Doubly Robust Estimator, theory and practice.

An End-to-End Implementation of AutoML with H2O, MLflow, FastAPI, and Streamlit for Insurance Cross-Sell

Serve, optimize and scale PyTorch models in production

[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)

Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

Code samples for my book "Neural Networks and Deep Learning"

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

TruthfulQA: Measuring How Models Imitate Human Falsehoods

Adaptive Experimentation Platform

Sketching data structures for scala, including t-digest

Automated Canary Service

🐢 bayesAB: Fast Bayesian Methods for A/B Testing

A curated list of causal inference libraries, resources, and applications.

Unstructured Code with interesting analysis

Helpful user defined fuctions / table generating functions for Hive

Statistical Bootstrap in Python

UpliftML: A Python Package for Scalable Uplift Modeling

This repository contains the slides of the FAU lecture Pattern Recognition

A python library for conducting interleaving, which compares two or multiple rankers based on observed user clicks by interleaving their results.

Automatically exported from code.google.com/p/smhasher

Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集

Answers to 120 commonly asked data science interview questions.

A repository to prepare you for your machine learning interview, involving most of the questions asked by all the tech giants and local companies. Do this to Ace your Machine Learning Engineer Inte…

Cracking the Coding Interview 6th Ed. Solutions

Python - 100天从新手到大师