1592 Open source projects that are alternatives of or similar to Chainer

Tensors and differentiable operations (like TensorFlow) in Rust

Fast implementation of BERT inference directly on NVIDIA (CUDA, CUBLAS) and Intel MKL

Several simple music synthesizers in Python 3. Input from ABC or MIDI files is also supported.

Monero (XMR) NVIDIA miner

Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python

Ngx - Neural network based visual generator and mixer

darknet neural network addon for openFrameworks

NVIDIA-accelerated zero latency video compression library for interactive remoting applications

This repository contains information about Cloud GPU offerings for Machine Learning practitioners.

Facebook's CUDA extensions.

An evolving guide to learning Deep Learning effectively.

Wind power visualization with WebGL particles

PyTorch for Numpy users. https://pytorch-for-numpy-users.wkentaro.com

Text Mining on the 2019 Mexican Government Report, covering from extracting text from a PDF file to plotting the results.

an Open Course Platform for Stanford CS224n (2020 Winter)

Julia support for native CUDA programming

RLgraph: Modular computation graphs for deep reinforcement learning

Digit recognition with Convolutional Neural Networks in WebGL

A TensorFlow-inspired neural network library built from scratch in C# 7.3 for .NET Standard 2.0, with GPU support through cuDNN

Learn CUDA Programming, published by Packt

Deep Reinforcement Learning for Keras.

Deep Learning Specialization by Andrew Ng on Coursera.

Implementation of Newcombe et al. CVPR 2015 DynamicFusion paper

A workshop for scientific computing in Python. ( December 2017 )

Introduction to Deep Neural Networks with Keras and Tensorflow

Fast Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...)

Vulkan compute for people

CuPy fused PyTorch neural networks ops

A collection of Bayesian data analysis recipes using PyMC3

macOS system monitor in your menu bar

General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python

These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.

A tiny hardware-accelerated pixel frame buffer. 🦀

Brain Simulator is a platform for visual prototyping of artificial intelligence architectures.

『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)

A wrapper around tensor2tensor to flexibly train, interact, and generate data for neural chatbots.

VUDA is a header-only library based on Vulkan that provides a CUDA Runtime API interface for writing GPU-accelerated applications.

Lab Materials for MIT 6.S191: Introduction to Deep Learning

🎨 Winning solution for the Painter by Numbers competition on Kaggle.

Machine learning algorithms for many-body quantum systems

Making it easier to work with shaders

Python module for performing basic dense linear algebra computations on the GPU using CUDA.

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Stereo Semi Global Matching by cuda

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)

A minimalist Deep Learning framework for embedded Computer Vision

DeepPose implementation in Chainer

Contains my explorations of TensorFlow 2.x

Python code to fuse multiple RGB-D images into a TSDF voxel volume.

Distribution-Aware Coordinate Representation for Human Pose Estimation

TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA

Intel® Graphics Compute Runtime for oneAPI Level Zero and OpenCL™ Driver

TensorFlow implementation of the Value Iteration Networks (NIPS '16) paper

A project for processing neural networks and rendering to gain insights on the architecture and parameters of a model through a decluttered representation.

A code generator for array-based code on CPUs and GPUs