Neural Networks
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Lecture materials and slides for the University of Oxford's 2017 advanced course on Deep Natural Language Processing.
A free and open-source face recognition library using deep neural networks for research and applications.
A collection of implementations and illustrative code accompanying DeepMind's published research papers across AI and machine learning.
A collection of implementations and illustrative code accompanying DeepMind's published research papers across AI and scientific domains.
GPU-accelerated neural network library for JavaScript, running in browsers and Node.js.
Open source implementation of AlphaFold 2, a deep learning system for highly accurate protein structure prediction.
A comprehensive JVM-based deep learning ecosystem for building, training, and deploying models with support for model import and distributed training.
Google's IPython Notebook demonstrating neural network art generation using the DeepDream technique.
A drop-in replacement for the MNIST dataset, featuring 70,000 Zalando fashion article images for benchmarking machine learning algorithms.
An unsupervised text tokenizer and detokenizer for neural network-based text generation systems with subword units.
A PyTorch library providing 12+ semantic segmentation model architectures with 800+ pretrained convolutional and transformer-based encoders.
A curated list of deep learning resources for computer vision, including papers, courses, books, and software.
A curated list of deep learning resources for computer vision, including papers, courses, books, and software.
An open-source Python toolkit for speaker diarization with state-of-the-art pretrained models and pipelines.
A curated repository of resources, datasets, and research papers for 3D machine learning, covering computer vision, graphics, and deep learning.
A TensorFlow 2 library providing simple, composable abstractions for machine learning research via the snt.Module concept.
An end-to-end speech processing toolkit for speech recognition, text-to-speech, translation, enhancement, and more.
A modular deep learning library providing a higher-level API for TensorFlow to speed up experimentation.
A Python library for flexible and readable tensor operations across numpy, PyTorch, JAX, TensorFlow, and other frameworks.
A collection of beginner-friendly TensorFlow tutorials with accompanying YouTube videos covering deep learning fundamentals and advanced topics.
A scientific computing framework with wide support for machine learning algorithms, built around multi-dimensional tensor operations.
An interactive visualization system for learning how Convolutional Neural Networks work through hands-on exploration.
A comprehensive guide to TensorFlow 2.x covering fundamentals, best practices, and advanced topics for efficient machine learning development.
WebGL-accelerated machine learning library for JavaScript with linear algebra and automatic differentiation.
A lightweight, modular, and scalable deep learning framework built on the original Caffe.
An end-to-end deep learning library focused on clear code and speed, used for research and production by Google Brain.
An end-to-end deep learning library focused on clear code, speed, and research, built by Google Brain.
Automatically differentiate native Python and NumPy code for gradient-based optimization and machine learning.
A curated list of papers, code, and resources for object detection algorithms in computer vision.
A TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers, offering customizable neural layers.
A TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers with customizable neural layers.
A customizable 3D platform based on Quake III for agent-based AI and deep reinforcement learning research.
A neural network library for JAX designed for flexibility, enabling researchers to experiment with new training forms by modifying training loops.
A neural network library for JAX designed for flexibility, enabling researchers to experiment with new training forms by modifying training loops.
A curated collection of standalone examples demonstrating machine learning tasks with TensorFlow.js in browsers and Node.js.
A high-performance neural network training interface for TensorFlow, optimized for speed and research flexibility.
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