Neural Networks
Showing 36 of 382 projects
A Haskell library for building and training feed-forward neural networks with automatic differentiation.
A deep learning model for classifying image aesthetic quality using Inception modules and fine-tuned connected layers.
A GPU-accelerated (CUDA) C++ template library for building and training artificial neural networks, including self-organizing maps and back-propagation networks.
A lightweight Clojure wrapper for TensorFlow's Java API, providing idiomatic access to machine learning operations.
A Swift library for accelerated tensor operations and dynamic neural networks with automatic differentiation, supporting all Apple platforms and Linux.
A small Clojure library for constructing and training neural networks using core.matrix.
A flexible deep learning framework for Ruby, ported from Python's Chainer.
A Clojure wrapper for Deeplearning4j, providing idiomatic access to neural networks, data import, and distributed training.
A Keras implementation of Ladder Networks for semi-supervised learning, achieving 98% accuracy on MNIST with only 100 labeled examples.
An experimental extension to Torch7's nn package, providing unproven neural network modules and optimizations.
A production-ready deep learning framework for Go that enables training and deploying neural networks as single binaries with a PyTorch-like API.
An all-in-one tool for creating, training, debugging, and sharing HTM neural networks using the original NuPIC library.
A collection of Jupyter notebooks for learning the neon deep learning framework through hands-on tutorials.
A deep learning system for automatic spoken language identification from audio files using TensorFlow and Caffe.
A lightweight, platform-independent tensor library with autograd for the JVM, accelerated by OpenCL.
A Delphi/Pascal binding for TensorFlow and Keras that enables Pascal developers to build, train, and deploy machine learning models.
A Clojure library for building and training neural networks with support for various architectures and learning algorithms.
Crystal language bindings for the FANN (Fast Artificial Neural Network) C library.
A neural network-based password cracking tool using character-level RNNs to learn and generate password guesses.
TensorFlow implementation of hierarchical attention networks for document classification using GRU cells and attention mechanisms.
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A pre-release Caffe branch for fully convolutional networks (FCNs), now deprecated with features merged into Caffe master.
A TensorFlow implementation of Attend, Infer, Repeat (AIR), a generative model for fast scene understanding by reconstructing objects sequentially.
A GUI-based tool for training deep neural networks to segment biological images using corrective annotation.
A modern, fast, and modular deep learning and machine learning framework for Python built on PyTorch.
A learning-focused, high-performance tensor computation library built from scratch in Rust with automatic differentiation and CPU/CUDA backends.
A neural network model that integrates neighbor information from heterogeneous networks to discover new drug-target interactions.
A Go implementation of the NEAT (NeuroEvolution of Augmenting Topologies) algorithm for evolving neural network structures.
A collection of neural network libraries for functional and mainstream languages, offering efficient lazy evaluation and cross-language compatibility.
A PyTorch-based tool for training custom DeepDream models using GoogleNet and custom image datasets.
A PyTorch-based Python library for energy-based machine learning models, including Restricted Boltzmann Machines and Deep Belief Networks.
A Common Lisp implementation for Llama inference operations, enabling LLM experimentation and integration with symbolic AI systems.
A Python library and CLI application for translating text using the DeepL neural machine translation service.
A deep learning algorithm that predicts type hints for Python code using neural networks.
ROS2 nodes for performing computer vision inference using TensorFlow models, enabling object detection and image classification in robotics.
A lightweight deep learning library written in C++ with C, C#, and Python interfaces, supporting CPU and GPU computation.
An interactive Swift PlaygroundBook that teaches neural network concepts through hands-on examples.
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