Showing 941-960 of 1,001 projects
A Python library for efficient and scalable data streaming for neural network training on PyTorch.
A Graph Neural Network Library in Jax for building AI-powered graph-based applications.
The official code repository for the second edition of the book Generative Deep Learning, covering AI models and techniques.
A comprehensive introduction to statistics and mathematics for data science, with a focus on the 'hacker' approach.
A Python library for computations and statistics on manifolds with geometric structures, useful for AI/ML developers.
A comprehensive Python library for time series forecasting using machine learning models.
This repository provides a collection of PyTorch tutorials, examples, and related books for developers interested in deep learning and AI.
A Python library for interpretable and explainable machine learning model analysis and visualization.
A collaboration workspace for Machine Learning, supporting popular ML frameworks and enabling reproducible workflows.
Open-source foundational library for training deep learning models with PyTorch.
A deep learning library for Haskell, enabling developers to build advanced AI models and applications.
AMD-SHARK Studio is a web UI for the SHARK+IREE high-performance machine learning distribution.
A deep learning toolkit for medical image analysis, supporting a variety of neural network models and medical imaging tasks.
A comprehensive collection of resources for learning machine learning in Russian.
Automated machine learning framework for creating and customizing ML models.
An implementation of DiffDock, a diffusion-based molecular docking method for binding prediction.
A curated list of 100+ resources for building and deploying generative AI, focused on helping you become a Generative AI Data Scientist.
Example Android app demonstrating how to use TensorFlow for machine learning on Android devices.
This is a comprehensive tutorial on linear algebra, designed for developers, with Python and visualization.
A curriculum for learning about foundation models, from scratch to the frontier for AI-focused developers.
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