Jeong-Yoon Lee

bartz. Super-fast BART (Bayesian Additive Regression Trees) in Python

gstack. Use Garry Tan's exact Claude Code setup: 23 opinionated tools that serve as CEO, Designer, Eng Manager, Release Manager, Doc Engineer, and QA

andrej-karpathy-skills. A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls.

basketball_analysis. 🏀 Basketball Video Analysis: Leverage automated detection and tracking of players, ball, and team assignments using advanced object tracking, zero-shot classification, and keypoint detection with YOLO models for comprehensive basketball game analysis

charting_reality_stochastic_modeling. Public materials for Charting Reality with Stochastic Modeling

managing-data-science-teams. Course materials for ECBS5256: Managing Data Science Teams - a workshop-driven intensive on analytics leadership at Central European University

notebooklm-py. Unofficial Python API and agentic skill for Google NotebookLM. Full programmatic access to NotebookLM's features—including capabilities the web UI doesn't expose—via Python, CLI, and AI agents like Claude Code, Codex, and OpenClaw.

meridian. Meridian is an MMM framework that enables advertisers to set up and run their own in-house models.

CATENets. Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.

ECC. The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

autograder_samples. Examples of autograders for running on Gradescope

causal-inference-in-python-code. Code for the Book Causal Inference in Python

hdmpy. The hdmpy package is a port of parts of the R package hdm

mini-swe-agent. The 100 line AI agent that solves GitHub issues or helps you in your command line. Radically simple, no huge configs, no giant monorepo—but scores >74% on SWE-bench verified!

MetricsMLNotebooks. Notebooks for Applied Causal Inference Powered by ML and AI

gemini-fullstack-langgraph-quickstart. Get started with building Fullstack Agents using Gemini 2.5 and LangGraph

reinforcement-learning-tutorials. Reinforcement Learning Algorithms Tutorial (Python) from scratch (Mar 2021)

causalml. Uplift modeling and causal inference with machine learning algorithms

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

samurai. Official repository of "SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory"

mixtape. Data and Program files for Causal Inference: The Mixtape

sports. computer vision and sports

kdd2024-workshop. KDD 2024 2nd Workshop on Causal Inference and Machine Learning in Practice

get-started-with-JAX. The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.

kaggler-template. Template for data science competitions. Includes makefiles and Python scripts for feature engineering, cross validation, ensemble, etc.

Writing_Speaking_Practice_AI. Jupyter Notebook

matched_markets. Matched Markets is a Python library for design and analysis of Geo experiments using Matched Markets and Time Based Regression.

VQASynth. Compose multimodal datasets 🎹

git-subrepo. Shell

nanoGPT. The simplest, fastest repository for training/finetuning medium-sized GPTs.

MVG. MVG = Minimum Viable Governance

conformal-metalearners. [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"

opensource.guide. 📚 Community guides for open source creators

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

xgen. Salesforce open-source LLMs with 8k sequence length.

kdd2023-workshop. KDD 2023 Workshop - Causal Inference and Machine Learning in Practice: Use cases for Product, Brand, Policy and Beyond

Robyn. Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.

Prompt-Engineering-Guide. 🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

tweet. Generate Tweet texts using OpenAI's GPT-3 based Davinci model

causica. Python

scpi. Synthetic Control Methods

CausalPy. A Python package for causal inference in quasi-experimental settings

RieszLearning. Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests"

engineeringladders. A framework for Engineering Managers

forest-confidence-interval. Confidence intervals for scikit-learn forest algorithms

amss. R

linearmodels. Additional linear models including instrumental variable and panel data models that are missing from statsmodels.

causal-forest. Implements the Causal Forest algorithm formulated in Athey and Wager (2018).

rbo. Implementation of Rank-biased Overlap

basketballVideoAnalysis. Jupyter Notebook

orthogonal_regularized_estimation. Code associated with paper: Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models, Chernozhukov, Nekipelov, Semenova, Syrgkanis, 2018

project-azua. Data Efficient Decision Making

causalml-feedstock. A conda-smithy repository for causalml.

keras. Deep Learning for humans

tfx. TFX is an end-to-end platform for deploying production ML pipelines

numpyro. Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

python-causality-handbook. Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

EconML. ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

caujax. Causal Jax

jax. Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

poetry. Python packaging and dependency management made easy

nice. Jupyter Notebook

upliftml. UpliftML: A Python Package for Scalable Uplift Modeling

SparseSC. Fit Sparse Synthetic Control Models in Python

PyFstat. a python package for gravitational wave analysis with the F-statistic

STFT_Transformer. Code for STFT Transformer used in BirdCLEF 2021 competition.

app_cloud_photos.

kaggle-birdclef-2021. Jupyter Notebook

Birdcall-Identification-competition. 2nd place in the Cornell Birdcall Identification competition

audiomentations. A Python library for audio data augmentation. Useful for making audio ML models work well in the real world, not just in the lab.

kaggle_birdcall_identification. 3rd Place Solution for the Cornell Birdcall Identification Kaggle Competition

kdd2021-tutorial. EconML/CausalML KDD 2021 Tutorial

counterfactual-cv. (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’

awesome-causal-inference. A (concise) curated list of awesome Causal Inference resources.

skgrf. scikit-learn compatible Python bindings for grf (generalized random forests) C++ random forest library

deeplearning. Jupyter Notebook

Denoise-Transformer-AutoEncoder. Python

treeboost_autograd. Easy Custom Losses for Tree Boosters using Pytorch

vae_cf. Variational autoencoders for collaborative filtering

EDLAE_NeurIPS2020. Jupyter Notebook

leetcode. C++

dynomite. A generic dynamo implementation for different k-v storage engines

masters-caesars-customer-gaming-prediction. Python

quora-question-pairs. Python

kddcup2019track1. Python

kddcup2019track2. Jupyter Notebook

cat-in-the-dat. 캐글 컴피티션 코드 정리 팁

data-science-glossary.

kaggler-tv-schedule. Kaggler TV

data-science-career-development. resources for career development in data science

tensorflow-tabnet. Improved TabNet for TensorFlow

av-for-concept-drift-in-automl. Code for Adversarial Validation Approach to Concept Drift Problem in Automated Machine Learning Systems

blog-archive. Jupyter Notebook

polynote. A better notebook for Scala (and more)

KRLPapers. Must-read papers on knowledge representation learning (KRL) / knowledge embedding (KE)

LightAutoML. LAMA - automatic model creation framework

dku-kaggle-class. 단국대 SW중심대학 2020년도 오픈소스SW설계 - 캐글뽀개기 수업 일정 및 강의자료

orbit. A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

machine-learning-systems-design. A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dmls-book`

super-linter. Combination of multiple linters to run as a GitHub Action or standalone

approachingalmost. Approaching (Almost) Any Machine Learning Problem

bbo_challenge_starter_kit. Starter kit for the black box optimization challenge at Neurips 2020

rexnet. Official Pytorch implementation of ReXNet (Rank eXpansion Network) with pretrained models

cudf. cuDF - GPU DataFrame Library

cuml. cuML - RAPIDS Machine Learning Library

fastbook. The fastai book, published as Jupyter Notebooks

Ax. Adaptive Experimentation Platform

optuna. A hyperparameter optimization framework

GW-BASIC. The original source code of Microsoft GW-BASIC from 1983

rich. Rich is a Python library for rich text and beautiful formatting in the terminal.

Pyro-M5-Starter-Kit. Learn Pyro through the M5 forecasting competition

TimeSeries_Seq2Seq. This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.

kaggle-web-traffic. 1st place solution

quadplay. The quadplay✜ fantasy console

kddcup-starting-kit. The submission template for the Learning to Dispatch and Reposition Competition @ KDD2020.

d2l-en. Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

data-mining-conferences. Ranking, acceptance rate, deadline, and publication tips

powerline. Powerline is a statusline plugin for vim, and provides statuslines and prompts for several other applications, including zsh, bash, tmux, IPython, Awesome and Qtile.

dscomp-winstab. Winner stability in data science competitions

AutoML-startingkit. AutoML-startingkit for NIPS 2018

pytorch-image-models. The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

minimal-mistakes. :triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.

manifold. A model-agnostic visual debugging tool for machine learning

Dongguk_AI_NLP_MachineTranslation. 동국대학교 영어영문학부 대상으로 진행하는 인공지능, 자연언어처리, 기계번역 강의자료

SleepCoacher. SleepCoacher recommendation engine, reference implementation for paper at http://jeffhuang.com/Final_SleepCoacher_UIST16.pdf

dragonnet. Python

awesome-causality-algorithms. An index of algorithms for learning causality with data

awesome-causality-algorithms. An index of algorithms for learning causality with data

justcause. 💊 Comparing causality methods in a fair and just way.

causal_inference_python_code. Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

autodl_starting_kit_stable. Starting kit for AutoCV/AutoDL challenge (https://autodl.chalearn.org)

ludwig. Low-code framework for building custom LLMs, neural networks, and other AI models

causallift. CausalLift: Python package for causality-based Uplift Modeling in real-world business

dowhy. DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

code-server. VS Code in the browser

BayesianOptimization. A Python implementation of global optimization with gaussian processes.

BISTRO-Starter-Kit. HTML

awesome-automl-papers. A curated list of automated machine learning papers, articles, tutorials, slides and projects

wtfpython. What the f*ck Python? 😱

kaggler-template. Template for data science competitions. Includes makefiles and Python scripts for feature engineering, cross validation, ensemble, etc.

MachineLearningNotebooks. Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

squeezedet-keras. Keras implementation of the Squeeze Det Object Detection Deep Learning Framework

keras-retinanet. Keras implementation of RetinaNet object detection.

examples. A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

pygbm. Experimental Gradient Boosting Machines in Python with numba.

NimbusML. Python machine learning package providing simple interoperability between ML.NET and scikit-learn components.

ml-train-deploy-vsts-k8s. A reference architecture for training and deploying machine learning models using best practice engineering and DevOps principles

MLAKSDeployment. How to deploy Python models on a Kubernetes cluster

AKSDeploymentTutorial. Tutorial on how to deploy Deep Learning models on GPU enabled Kubernetes cluster

VGGish. An inplementation of vggish in keras with tf backend

fox-audio. Python

EdgeML. This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.

codalab-dockers.

reverb-ml. 🔊📊 An Electron app to play, visualize, label, and slice your audio files

audioset_classification. Python

VGGish. An implementation of vggish in keras with tf backend

aztk. AZTK powered by Azure Batch: On-demand, Dockerized, Spark Jobs on Azure

auto_reply. 플러스친구 자동응답 API

cs230-code-examples. Code examples in pyTorch and Tensorflow for CS230

DLTK. Deep Learning Toolkit for Medical Image Analysis

supervision-by-registration. Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors

landmark-detection. Four landmark detection algorithms, implemented in PyTorch.

face-alignment. :fire: 2D and 3D Face alignment library build using pytorch

2D-and-3D-face-alignment. This repository implements a demo of the networks described in "How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)" paper.

mlflow. The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.

awesome-ai. A curated list of artificial intelligence resources (Courses, Tools, App, Open Source Project)

the-state-of-ai. This repository compiles latest discussions and resources around the state of artificial intelligence (AI). Any contributions are welcome.

NLP-progress. Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

google-images-download. Python Script to download hundreds of images from 'Google Images'. It is a ready-to-run code!

spotlight. Deep recommender models using PyTorch.

triplet_recommendations_keras. An example of doing MovieLens recommendations using triplet loss in Keras

cbvrp-acmmm-2018. cbvrp-acmmm-2018

DataSciComp. A collection of popular Data Science Challenges/Competitions || Countdown timers to keep track of the entry deadlines.

fastai_deeplearn_part1. Notes for Fastai Deep Learning Course

LOUPE. Tensorflow toolbox implementing several learnable pooling architecture

fastai. The fastai deep learning library

LibFM_in_Keras. This notebook shows how to implement LibFM in Keras and how it was used in the Talking Data competition on Kaggle.

easy-tensorflow-multimodel-server. Simple to run server for multiple TensorFlow Object Detection models

tensorflow-object-detection. 📦 Operationalizing TensorFlow Object Detection on Azure

tensorflow-k8s-azure. Train TensorFlow Models at Scale with Kubernetes and Kubeflow on Azure

CVWorkshop-Deprecated-. This workshop has been deprecated check out the new workshop here https://github.com/aribornstein/cvworkshop

jupyterlab. JupyterLab computational environment.

Detectron. FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

BatchAI. Repo for publishing code Samples and CLI samples for BatchAI service

implicit. Fast Python Collaborative Filtering for Implicit Feedback Datasets

Tensorflow-Project-Template. A best practice for tensorflow project template architecture.

models. Models and examples built with TensorFlow

kaggle-cli. Official Kaggle CLI

traceml. Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

jupyter-themes. Custom Jupyter Notebook Themes

entity-embedding-rossmann. Jupyter Notebook

xlearn. High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

textClassifier. Text classifier for Hierarchical Attention Networks for Document Classification

crowdai-criteo-ad-placement-challenge-starter-kit. Starter kit for getting started in the NIPS 2017 Criteo Ad Placement Challenge

DeepLearningFrameworks. Demo of running NNs across different frameworks

baseline. Python

blockchain-notes.

Wordbatch. Python library for distributed AI processing pipelines, using swappable scheduler backends.

Kaggle-Carvana-Image-Masking-Challenge. Solution based on U-Net for the Kaggle Carvana Image Masking Challenge

instacart-basket-prediction. Kaggle | Instacart Market Basket Analysis🥕🥉