Machine Learning
Showing 36 of 601 projects
A highly efficient, scalable Gaussian process library implemented in PyTorch with GPU acceleration and modular design.
Intel's reference deep learning framework designed for high performance across CPUs, GPUs, and custom hardware.
A MATLAB/Octave toolbox for deep learning with implementations of neural networks, deep belief nets, autoencoders, and convolutional networks.
Enables distributed TensorFlow training and inferencing on Apache Spark and Hadoop clusters with minimal code changes.
A curated list of 100 foundational and influential papers in natural language processing for students and researchers.
A curated list of open-source tools for professional robotic development in C++ and Python, covering ROS, autonomous driving, and aerospace.
An open-source, locally-runnable code completion engine using large language models that works on CPU.
A collection of Jupyter notebooks accompanying a 10-part video series teaching machine learning with Python's scikit-learn library.
Fast Python library for collaborative filtering recommendation algorithms on implicit feedback datasets.
R code examples from the 'Machine Learning for Hackers' book, demonstrating practical machine learning techniques.
A Java dataframe and visualization library for data loading, cleaning, transformation, and analysis.
A Python library for self-supervised learning on images, providing a modular PyTorch-like framework with support for modern SSL models.
An open-source platform for building, training, and monitoring large-scale deep learning applications with full lifecycle MLOps.
An end-to-end platform for applied reinforcement learning and contextual bandits, originally developed at Facebook for production recommendation systems.
A collection of handwritten notes, notebooks, and resources for Andrew Ng's Deep Learning Specialization on Coursera.
A C#/.NET library for efficient local inference of LLaMA and other large language models, based on llama.cpp.
The fastest way to build data pipelines with iterative development and deployment anywhere.
A TensorFlow project template with a well-designed folder structure and OOP design to accelerate deep learning development.
A curated collection of high-quality resources for quantitative and algorithmic trading with a focus on machine learning applications.
A toolkit for turning classic video games into Gym environments for reinforcement learning research.
A curated collection of research papers and resources on Vision Transformers (ViT) for computer vision tasks.
A neural network that automatically adds color to grayscale images using deep learning techniques.
A web-based IDE for machine learning and data science with pre-installed libraries and tools, deployable via Docker.
A Python library for probabilistic modeling built on PyTorch, offering modular distributions, GPU support, and flexible model composition.
A modular library for Bayesian optimization built on PyTorch, enabling efficient optimization of expensive black-box functions.
A procedural Blender pipeline for generating photorealistic training images for computer vision and machine learning.
A PyTorch-based framework for visual object tracking and video object segmentation, featuring implementations of state-of-the-art trackers like TaMOs, RTS, and DiMP.
Human Activity Recognition using TensorFlow and LSTM RNNs on smartphone sensor data to classify six movement types.
Human Activity Recognition using TensorFlow and LSTM RNNs on smartphone sensor data to classify six movement types.
Seamlessly integrate large language models like ChatGPT into scikit-learn for enhanced text analysis tasks.
A debugging and visualization tool for data science, deep learning, and reinforcement learning in Jupyter Notebook.
A tiny and efficient C++/Python binding library with faster compilation, smaller binaries, and lower runtime overhead than pybind11.
A distributed system for learning graph embeddings from large-scale graphs with billions of entities and trillions of edges.
A numerical processing library for Scala, providing generic, clean, and powerful linear algebra and scientific computing capabilities.
A comprehensive collection of machine learning tutorials and implementations in Python, covering algorithms from scratch to production deployment.
A curated list of Generative AI tools, models, artworks, and educational resources.
Related Tags
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.