Deep Learning
Showing 36 of 774 projects
A family of open-source deep learning models for accurate biomolecular interaction and binding affinity prediction, rivaling AlphaFold3 and physics-based methods.
A curated list of resources for action recognition, video understanding, object detection, and pose estimation in computer vision.
An open-source cross-platform performance library of basic building blocks for deep learning applications, optimized for CPUs and GPUs.
A Unity-based simulator for training self-driving car models using deep learning.
A curated list of satellite and aerial imagery datasets with annotations for computer vision and deep learning tasks.
A MATLAB/Octave toolbox for deep learning with implementations of neural networks, deep belief nets, autoencoders, and convolutional networks.
Intel's reference deep learning framework designed for high performance across CPUs, GPUs, and custom hardware.
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 JAX library for rapid prototyping of large-scale attention-based vision models across images, video, audio, and multimodal data.
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.
A collection of handwritten notes, notebooks, and resources for Andrew Ng's Deep Learning Specialization on Coursera.
A curated collection of high-quality resources for quantitative and algorithmic trading with a focus on machine learning applications.
A TensorFlow project template with a well-designed folder structure and OOP design to accelerate deep learning development.
A comprehensive Python-first reinforcement learning framework with modular abstractions for decision intelligence applications.
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 PyTorch-based framework for visual object tracking and video object segmentation, featuring implementations of state-of-the-art trackers like TaMOs, RTS, and DiMP.
Seamlessly integrate large language models like ChatGPT into scikit-learn for enhanced text analysis tasks.
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.
Implementation of SRGAN for photo-realistic single image super-resolution using generative adversarial networks.
A debugging and visualization tool for data science, deep learning, and reinforcement learning in Jupyter Notebook.
A curated list of Generative AI tools, models, artworks, and educational resources.
Automatic and interactive image colorization using deep neural networks, with PyTorch models for ECCV 2016 and SIGGRAPH 2017 papers.
A curated list of Python software for data science, covering machine learning, deep learning, visualization, and data manipulation.
A comprehensive collection of machine learning tutorials and implementations in Python, covering algorithms from scratch to production deployment.
A neural network library optimized for dynamic structures that change per training instance, with C++ and Python bindings.
A PyTorch framework for deep learning research and development, focusing on reproducibility and rapid experimentation.
A trainable, memory-efficient PyTorch reproduction of AlphaFold 2 for protein structure prediction.
A deep learning library for audio and music analysis, providing time-frequency transforms and feature extraction for tasks like classification and MIR.
A modular TensorFlow library for applied reinforcement learning with a focus on flexible design and practical usability.
A modular TensorFlow library for applied reinforcement learning with a focus on flexible design and practical usability.
A library of differentiable digital signal processing functions for interpretable audio synthesis in deep learning models.
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