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applied-ml
๐ Papers & tech blogs by companies sharing their work on data science & machine learning in production.open-llms
๐ A list of open LLMs available for commercial use.ml-surveys
๐ Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.ml-design-docs
๐ Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)1-on-1s
๐ฑ 1-on-1 questions and resources from my time as a manager.testing-ml
๐ Minimal examples of machine learning tests for implementation, behaviour, and performance.obsidian-copilot
๐ค A prototype assistant for writing and thinkingapplyingml
๐ Papers, guides, and mentor interviews on applying machine learning for ApplyingML.comโthe ghost knowledge of machine learning.papermill-mlflow
๐งช Simple data science experimentation & tracking with jupyter, papermill, and mlflow.python-collab-template
๐ Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.recsys-nlp-graph
๐ Simple recommender with matrix factorization, graph, and NLP. Beating the regular collaborative filtering baseline.llm-paper-notes
Notes from the Latent Space paper club. Follow along or start your own!fastapi-html
Sample repository demonstrating how to use FastAPI to serve HTML web apps.eugeneyan
poc-docker-template
Simple template showing how to set up docker for reproducible data science with Jupyter notebooks.text-to-image
nocode-ml
๐ End-to-end machine learning; "no code" required!learning-typescript
design-patterns
deep-rl
Repository for deep reinforcement learning with OpenAItesting-pipelines
kaggle_springleaf
Code for Kaggle Springleaf Email Prediction ChallengeComputational-Thinking-and-Data-Science
edX: Introduction to Computational Thinking and Data Science (Oct 2014)ama
Ask Me AnythingMining-Massive-Datasets
Coursera: Mining Massive Datasets (Sep 2014)Time-Series-Analysis
Simple forecasting with Regression Modelraspberry-llm
Calling LLM APIs on a Raspberry Pi for lulzStatistical-Inference
This repository contains the lab assignments for the facilitation of John Hopkins University' Coursera MOOC on Statistical Inference.kaggle_titanic
Code for Kaggle Titanic Challenge (and other learning)Statistical-Learning
Stanford OpenX: Introduction to Statistical LearningData-Analysis-and-Statistical-Inference-Project
Coursera: Data Analysis & Statistical Inference Project (Feb 2014)neural_networks_and_deep_learning
Twitter-SMA
Twitter Streaming and Analysis with Python and Rscratch
Getting-and-Cleaning-Data
Coursera: Getting and Cleaning Data (May 2014)Computer-Science-and-Programming-In-Python
edX: Introduction to Computer Science and Programming in Python (July 2014)Misc
datagene
Interactive-Programming-in-Python
Coursera: Interactive Programming in Python (Apr 2014)R-Programming
Coursera: R Programming (May 2014)Visualizations
Random Visualizationsjson-to-utterances
DKSG-HOME
Sharing my R script used in the DKSG DataLearn for homeeugeneyan-comments
kaggle_otto
Code for Kaggle Otto Production Classification ChallengeDemand-Forecasting
Prototyping various forecasting techniquesMachine-Learning
Coursera: Machine Learning (Aug 2014)Love Open Source and this site? Check out how you can help us