Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Core deep-learning frameworks and libraries for pretraining and distributed training.
Signals: deep-learning, neural-network, pytorch, tensorflow, jax, distributed-training, training, deepspeed
2,663 results
Machine learning framework for Node.js.
An end-to-end machine learning and data mining framework on Hadoop
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning
Personal short implementations of Machine Learning papers
MindMaker UE4 Machine Learning Toolkit
🤖 A curated list of machine learning & artificial intelligence startups in Berlin (Germany)
机器学习工程师、算法工程师、软件工程师、数据科学家-面试指南 | Interview guide for MLE, SDE, DS
Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression
Implementation of a single layer of the MMDiT, proposed in Stable Diffusion 3, in Pytorch
[ICLR 2024] Controlling Vision-Language Models for Universal Image Restoration. 5th place in the NTIRE 2024 Restore Any Image Model in the Wild Challenge.
Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifically, recipes aims to provide- Consistent access to pre-trained SOTA models ready for production- Reference implementations for SOTA research reproducibility, and infrastructure to guarantee correctness, efficiency, and interoperability.
The collaborative real-time open-source machine learning devtool and training suite: Experiment execution, tracking, and debugging. With server and project management tools.
We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.
Framework for defining machine learning models, including feature generation and transformations, as directed acyclic graphs (DAGs).
Repository of code and resources related to different data science and machine learning topics. For learning, practice and teaching purposes.
Neo-AI-DLR is a common runtime for machine learning models compiled by AWS SageMaker Neo, TVM, or TreeLite.
A high-level, rapid development framework for machine learning projects
Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax).
Enterprise graph machine learning framework for billion-scale graphs for ML scientists and data scientists.
List of resources & possible pathway for the Math of Machine Learning and AI.
A High-level Machine Learning Library for Go
Tool that predicts the outcome of a Dota 2 game using Machine Learning
An Open-Source Machine Learning Framework in Rust Δ
Machine Learning Environment - alpha version
24,545 repositories in the index in total.
