🧑🏫 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
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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.
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
Open standard for machine learning interoperability
Machine Learning Engineering Open Book
🦉 Data Versioning and ML Experiments
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
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)
The Open Source Feature Store for AI/ML
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Accelerated deep learning R&D
StellarGraph - Machine Learning on Graphs
Algorithms for explaining machine learning models
A curated list of community detection research papers with implementations.
An intuitive library to add plotting functionality to scikit-learn objects.
An open source library and framework for deep learning on satellite and aerial imagery.
Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
Interpretability and explainability of data and machine learning models