Artificial neural networks (ANN) are computational systems that "learn" to perform tasks by considering examples, generally without being programmed with any task-specific rules.
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
An Open Source Machine Learning Framework for Everyone
Tensors and Dynamic neural networks in Python with strong GPU acceleration
On-device Neural Engine
🧙 Bitcoin Hodl Prophet
Music suggestions for users based either on a custom-built algorithm from song input or emotion detection from face through live camera feed.
High performance PHP autograd (automatic differentiation) with GPU support.
An animal can do training and inference every day of its existence until the day of its death. A forward pass is all you need.
The Sakata Index is a technical indicator that uses neural network.
Create flowcharts of neural networks and convert the flowcharts into PyTorch for inferencing/training.
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
AI with Python
On-device AI across mobile, embedded and edge for PyTorch
The collection of pre-trained, state-of-the-art AI models for ailia SDK
Visualizer for neural network, deep learning and machine learning models
A curated list of classic artificial intelligence paper
Introduction to neural networks - from scratch.
Livermore Big Artificial Neural Network Toolkit
This is just a reprository to track my progress in learning pytorch.
A versatile application for building, training, and visualizing neural networks with PyQt5. This tool supports Feedforward, Convolutional, and Recurrent Neural Networks. Features include layer customization, CSV input, model saving/loading, and training loss visualization. Ideal for neural network experimentation and educational purposes.