Pytorch domain library for recommendation systems

FB (Facebook) + GEMM (General Matrix-Matrix Multiplication) - https://code.fb.com/ml-applications/fbgemm/

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

Sky-T1: Train your own O1 preview model within $450

the AI-native open-source embedding database

Hidden Markov Models in Python, with scikit-learn like API

Parallel Hyperparameter Tuning in Python

Open source implementation of AlphaFold3

Code for 1st place solution to Kaggle's Abstraction and Reasoning Challenge

Abstract Reasoning with Graph Abstractions (ARGA) implementation

A deep dive into embeddings starting from fundamentals

Chronos: Pretrained Models for Probabilistic Time Series Forecasting

Plain python implementations of basic machine learning algorithms

code for CVPR2024 paper: DiffMOT: A Real-time Diffusion-based Multiple Object Tracker with Non-linear Prediction

Kolmogorov Arnold Networks

Data package for Nasdaq listings

The official PyTorch implementation of Google's Gemma models

We write your reusable computer vision tools. 💜

Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…

A recommender system for Wikipedia pages.

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

A list of blogs, videos, and other content that provides advice on building experimentation and A/B testing platforms

Python class to scrape data from rightmove.co.uk and return listings in a pandas DataFrame object

A collection of stand-alone Python machine learning recipes

Bayesian Modeling and Probabilistic Programming in Python

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 ;)

Fit data to many distributions

Official implementation of our NeurIPS 2023 paper "Augmenting Language Models with Long-Term Memory".