🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Repository Index
47,133 repositories indexed
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Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
Streamlit — A faster way to build and share data apps.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Open standard for machine learning interoperability
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
:satellite: All You Need to Know About Deep Learning - A kick-starter
Accelerated deep learning R&D
StellarGraph - Machine Learning on Graphs
A curated list of community detection research papers with implementations.
An open source library and framework for deep learning on satellite and aerial imagery.
Interpretability and explainability of data and machine learning models
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.
Maze Applied Reinforcement Learning Framework