Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Repository for our ICLR 2023 paper: DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems

real time face swap and one-click video deepfake with only a single image

Massively parallel rigidbody physics simulation on accelerator hardware.

LangServe 🦜️🏓

Contains Python scripts for Exploratory Data Analysis, Algorithms Evaluation, and so on.

Contains the code and guides for the course Introduction to Intelligent and Autonomous Systems

JADE Java Agent DEvelopment platform 4.6.1, rev6874 (2023/07/11) builded with Apache Maven 3.9.6 (2024-03-12) and Java 17.0.2, Oracle Corporation

Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable…

Sequential Decision Problem Modeling Library @ Castle Lab, Princeton Univ.

Large scale simulations made simple.

32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

The fastai book, published as Jupyter Notebooks

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

Python Data Science Handbook: full text in Jupyter Notebooks

Solving the Traveling Salesman Problem using Self-Organizing Maps

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Powerful .NET library for benchmarking

This repository has examples of broken patterns in ASP.NET Core applications

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"

Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)

A collection of libraries to optimise AI model performances

Project for Learning to Rank using RankNet, LambdaRank and LambdaMART

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

In this project, we combined quantum computing with reinforcement learning and studied its application to a board game to assess the benefits that it can introduce, namely its impact on the learnin…

This project aims to create an implementation of the tail assignment problem using a quantum computing approach.

Content recommendation based on user preferences using IRL