Deep Learning
Showing 36 of 937 projects
An open-source machine learning framework for building classical, deep, or hybrid ML applications with a focus on performance and portability.
Rust bindings for the C++ API of PyTorch, providing thin wrappers around libtorch.
Rust language bindings for TensorFlow, providing idiomatic access to machine learning capabilities.
A fast, flexible C++ standalone library for machine learning with high-performance defaults and total internal modifiability.
A fast, flexible C++ standalone library for machine learning with high-performance defaults and total internal modifiability.
A curated collection of papers, code, and resources for domain adaptation in machine learning.
A local-first, ML-powered desktop application for translating manga, built in Rust with automated text detection, OCR, inpainting, and LLM translation.
A TensorFlow implementation of DeepMind's WaveNet neural network for generating raw audio waveforms.
DeepMind's library for building graph networks in TensorFlow and Sonnet, enabling graph-structured data processing with neural networks.
Code repository for the 'Machine Learning with PyTorch and Scikit-Learn' book, providing practical examples and notebooks.
A curated list of open-source geospatial analysis tools, libraries, and resources across multiple programming languages and domains.
An open-source library for building massively scalable machine learning pipelines on Apache Spark.
A fully convolutional neural network for real-time instance segmentation, achieving high speed and accuracy on COCO.
A compiler that extends SQL with AI capabilities to train, predict, and evaluate machine learning models directly from SQL statements.
A Python library for image augmentation in machine learning, offering a stochastic pipeline approach with fine-grained control over operations.
A hands-on beginner's guide to machine learning and image classification using Caffe and DIGITS with neural networks.
A curated list of awesome Generative Adversarial Network (GAN) applications and demonstrations across various domains.
A curated collection of links to conference publications, surveys, and software in graph-based deep learning.
A library of optimized communication primitives for multi-GPU and multi-node collective operations.
Run trained Keras models directly in the browser with GPU acceleration via WebGL.
A highly-accurate, lightweight, on-device wake word detection engine powered by deep learning.
A Python module for easily training character- or word-level text-generating neural networks on any dataset with minimal code.
An engine-agnostic deep learning framework for Java developers, providing a high-level API for model training and inference.
A curated collection of graph classification papers with implementations covering embeddings, deep learning, kernels, and factorization.
A curated collection of graph classification papers with reference implementations covering embedding, deep learning, kernels, and factorization.
A high-level library for training and evaluating neural networks in PyTorch with a flexible engine and event system.
A curated collection of academic papers covering all aspects of face analysis, including detection, recognition, alignment, generation, and anti-spoofing.
A collection of infrastructure and tools for research in neural network interpretability and visualization.
A JAX implementation of OpenAI's Whisper model offering up to 70x faster transcription on TPUs.
A curated collection of Python libraries, tutorials, and tools for data science, from data wrangling to machine learning and visualization.
:satellite: All You Need to Know About Deep Learning - A kick-starter
A PyTorch-based research platform implementing state-of-the-art single object tracking algorithms like SiamRPN and SiamMask.
A unified, comprehensive, and efficient Python/PyTorch library for reproducing and developing recommendation algorithms.
:earth_americas: Simple and ready-to-use tutorials for TensorFlow
Official PyTorch implementation of HRNet for human pose estimation, maintaining high-resolution representations through parallel multi-scale fusions.
A library for probabilistic reasoning and statistical analysis integrated with TensorFlow and JAX.
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