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Pytorch domain library for recommendation systems
FB (Facebook) + GEMM (General Matrix-Matrix Multiplication) - https://code.fb.com/ml-applications/fbgemm/
A scikit-learn-compatible module to estimate prediction intervals and control 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
The official PyTorch implementation of Google's Gemma models
We write your reusable computer vision tools. đź’ś
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 ;)
Official implementation of our NeurIPS 2023 paper "Augmenting Language Models with Long-Term Memory".