Deep Learning
Showing 36 of 937 projects
An open-source simulator for experimenting with and advancing self-driving AI, accessible to anyone with a PC.
A CPU and GPU-accelerated machine learning library optimized for high-performance computing.
A distributed platform for rapid deep learning application development with neural network engine and Hadoop integration.
A curated list of face-related algorithms, datasets, papers, and open-source libraries for computer vision research.
A PyTorch implementation of Social GAN for predicting socially acceptable human trajectories using generative adversarial networks.
TensorFlow implementation of an attention-based neural image caption generator that focuses on relevant image parts while generating words.
A Go interface for importing and executing pre-trained ONNX neural network models without framework dependencies.
A C++ recurrent neural network library for sequence learning problems, specializing in online handwriting prediction and synthesis.
A collection of transformer-based foundation models for genomics and transcriptomics, enabling tasks like sequence analysis, functional prediction, and conversational DNA exploration.
GPU-accelerated Python implementation of six fundamental deep learning algorithms using CUDA libraries.
CVPR 2015 workshop materials for learning deep learning and computer vision with Torch framework.
Convert PyTorch models to Keras (TensorFlow backend) for deployment and interoperability.
TensorFlow implementation of unsupervised cross-domain image generation for transferring images between domains like SVHN to MNIST.
A PyTorch implementation of neural style transfer, combining the content of one image with the artistic style of another.
A curated collection of papers, code, and datasets for deep learning and multimodal learning in video analysis.
A visible-infrared paired dataset for low-light vision tasks like pedestrian detection, image fusion, and image-to-image translation.
A minimal 200-line implementation of a sequence-to-sequence chatbot using TensorLayer and TensorFlow.
A Bitcoin trading bot using deep reinforcement learning (TensorForce) to automate buy/sell/hold decisions based on price history.
A Ruby deep learning library powered by LibTorch, providing a PyTorch-like API for Ruby developers.
A deep learning library for Ruby that provides a native interface to LibTorch, enabling GPU-accelerated neural network development.
A chess AI that learns to play chess using deep learning and neural networks.
A Ruby API for TensorFlow, enabling machine learning and deep learning within Ruby applications.
A curated list of research papers and resources for scene understanding in computer vision, covering 3D reconstruction, layout estimation, and primitive detection.
A Python package for applying graph neural networks to molecular graphs and biological networks in life science research.
A comprehensive Swift framework providing AI/ML algorithms including neural networks, SVMs, PCA, genetic algorithms, and MDPs with GPU acceleration support.
A comprehensive Swift framework providing AI/ML algorithms including neural networks, SVMs, genetic algorithms, and MDPs with GPU acceleration.
A PyTorch framework for semantic segmentation of large 3D point clouds using superpoint graphs.
A long-range genomic foundation model that processes DNA sequences up to 1 million nucleotides at single nucleotide resolution.
A Python project for algorithmic music generation using recurrent neural networks.
A modular deep learning framework for PyTorch to build neural networks on heterogeneous tabular data.
A TensorFlow implementation for generating semantically segmented bird's eye view images from multiple vehicle-mounted cameras using a Sim2Real deep learning approach.
:speaker: Deep Learning & 3D Convolutional Neural Networks for Speaker Verification
TensorFlow implementation of character-aware neural language models using CNN, highway networks, and LSTM.
A PyTorch and TorchDrug based deep learning library for drug pair scoring, predicting interactions, side effects, and synergy.
A collection of tutorials and resources to help developers learn JAX, Flax, and Haiku for machine learning.
An object-oriented machine learning framework built on JAX, designed for simplicity and readability in research.
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.