Neural Networks
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An end-to-end open source platform for machine learning with a comprehensive ecosystem of tools and libraries.
An end-to-end open source platform for machine learning with a comprehensive ecosystem of tools and libraries.
A Python package for tensor computation with GPU acceleration and dynamic neural networks built on a tape-based autograd system.
A collection of 60+ annotated PyTorch implementations of deep learning papers with side-by-side explanatory notes.
A multi-backend deep learning framework that enables effortless model development across JAX, TensorFlow, PyTorch, and OpenVINO.
A state-of-the-art PyTorch-based computer vision model for object detection, segmentation, and classification.
A deep learning toolkit for Text-to-Speech generation with pretrained models in over 1100 languages and tools for training.
A comprehensive collection of TensorFlow tutorials and examples for beginners, covering both TF v1 and v2 with clear explanations.
A fast open framework for deep learning with a focus on expression, speed, and modularity.
A collection of concise PyTorch tutorials for deep learning researchers, with most models implemented in under 30 lines of code.
Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility and transparency.
A curated list of awesome deep learning tutorials, projects, and communities.
A curated list of awesome deep learning tutorials, projects, and communities.
A deep learning library built on PyTorch that provides high-level components for rapid results and low-level components for research flexibility.
A deep learning library built on PyTorch that provides high-level components for rapid results and low-level components for research flexibility.
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
LaTeX code and Python interface for creating publication-quality neural network architecture diagrams.
Python implementations of popular machine learning algorithms from scratch with interactive Jupyter demos and mathematical explanations.
A repository of examples, utilities, and best practices for building and deploying production-ready recommendation systems.
An open standard format for representing machine learning models to enable interoperability between frameworks.
A cross-platform, high-performance accelerator for machine learning inference and training with ONNX models.
A flexible and efficient deep learning framework that mixes symbolic and imperative programming for heterogeneous distributed systems.
A flexible and efficient deep learning framework that mixes symbolic and imperative programming for heterogeneous distributed systems.
A flexible and efficient deep learning framework that mixes symbolic and imperative programming for heterogeneous distributed systems.
A minimalist, high-performance machine learning framework for Rust with a focus on serverless inference and GPU support.
A research project exploring machine learning for generating music, images, and art using deep learning and reinforcement learning.
A hardware-accelerated JavaScript library for training and deploying machine learning models in browsers and Node.js.
A hardware-accelerated JavaScript library for training and deploying machine learning models in the browser and Node.js.
A curated collection of tutorials, articles, and resources for learning machine learning and deep learning topics.
A topic-wise curated list of machine learning and deep learning tutorials, articles, and resources for developers and data scientists.
A PyTorch library providing datasets, model architectures, and image transformations for computer vision tasks.
Code samples and implementations from the book 'Neural Networks and Deep Learning' for educational purposes.
A unified deep learning toolkit for describing neural networks as computational graphs, supporting feed-forward DNNs, CNNs, and RNNs/LSTMs.
A curated list of awesome TensorFlow experiments, libraries, projects, tutorials, and resources.
A curated list of awesome TensorFlow experiments, libraries, projects, tutorials, and resources.
A comprehensive collection of machine learning algorithms implemented exclusively in NumPy for educational purposes and prototyping.
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