Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Updated
May 23, 2024 - Python
Tensors and Dynamic neural networks in Python with strong GPU acceleration
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
An Engine-Agnostic Deep Learning Framework in Java
An autograd engine built for my understanding
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
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.
The Unified AI Framework
A Machine Learning framework from scratch in Pure Mojo 🔥
Automatic differentiation for tensor operations
『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)
Sharp Grad is a lightweight automatic differentiation library in C#. It's suitable for implementing machine learning algorithms, scientific computations, and any applications that require gradient-based optimization.
A minimal OpenCL, CUDA, Vulkan and host CPU array manipulation engine / framework.
toydl: toy deep learning algorithms implementation, backend with self implement toy torch
Owl - OCaml Scientific Computing @ https://ocaml.xyz
Deep Learning Framework Written in Rust
Error propagation and statistical analysis for Markov chain Monte Carlo simulations in lattice QCD and statistical mechanics using autograd
PyTorch but for GigaChads, GigaTorch.
Simple Documentation Builder for Ivy Projects.
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