Best Papers of Top Venues like CVPR, NeurIPS, ICLR, ICML, ICCV, ECCV, ...

A python library for self-supervised learning on images.

LLM training in simple, raw C/CUDA

🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming

Opiniated RAG for integrating GenAI in your apps 🧠 Focus on your product rather than the RAG. Easy integration in existing products with customisation! Any LLM: GPT4, Groq, Llama. Any Vectorstore: …

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

ZenML 🙏: The bridge between ML and Ops. https://zenml.io.

GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

The open-source library for explainable AI. Generic and easy to integrate with PyTorch.

The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.

A curated list of references for MLOps

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Instant neural graphics primitives: lightning fast NeRF and more

Uniform Manifold Approximation and Projection

A hyperparameter optimization framework

🙃 A delightful community-driven (with 2,400+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, python…

A complete computer science study plan to become a software engineer.

Cross-platform, customizable ML solutions for live and streaming media.

Split your file into encrypted fragments so that you don't need to remember a passcode

Data science interview questions and answers

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Papers & presentation materials from Hugging Face's internal science day

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

A wrapper of the COCOeval class for extended keypoint error estimation analysis.

A PyTorch re-implementation of CPN (Cascaded Pyramid Network for Multi-Person Pose Estimation)

TensorDash is an application that lets you remotely monitor your deep learning model's metrics and notifies you when your model training is completed or crashed.