Tensors and Dynamic neural networks in Python with strong GPU acceleration
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autograd
Repositories 29
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation
A C++ standalone library for machine learning
C++
Updated Apr 3, 2019
Owl - OCaml Scientific and Engineering Computing @ http://ocaml.xyz
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via…
Notes, examples, and Python demos for the textbook "Machine Learning Refined" (Cambridge University Press).
machine-learning
deep-learning
artificial-intelligence
data-science
jupyter-notebook
numpy
autograd
machine-learning-algorithms
lecture-notes
slides
neural-network
Python
Updated Apr 2, 2019
Tiny and elegant deep learning library
Python
Updated Feb 12, 2019
Julia port of the Python autograd package.
Julia
Updated Mar 23, 2019
PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations
Python
Updated Mar 22, 2019
Torch Containers simplified in PyTorch
Lua
Updated Apr 28, 2017
scorch is a deep learning framework in Scala inspired by PyTorch
Scala
Updated Apr 4, 2019
Image registration laboratory for 2D and 3D image data
Python
Updated Feb 26, 2019
Tensors and differentiable operations (like TensorFlow) in Rust
Rust
Updated Mar 25, 2019
Kotlin𝛁: Differentiable Functional Programming with Algebraic Data Types
automatic-differentiation
differentiable-programming
autograd
backpropagation
computer-algebra
algebra
functional-programming
kotlin
TeX
Updated Apr 2, 2019
Deep-Learning framework from scratch
Python
Updated Oct 13, 2018
A pure-python/numpy autograd tensor library
用例子学习PyTorch1.0(Learning PyTorch with Examples 中文翻译与学习)
Jupyter Notebook
Updated Mar 11, 2019
Autograd (backpropagation, reverse-mode auto differentiation) in Nim
Nim
Updated Oct 25, 2017
A collection of tree data structures, SARSA, and autograd, Work in Progress
Rust
Updated Mar 26, 2019
Qualia2.0 is a deep learning framework deeply integrated with automatic differentiation and dynamic graphing with CUD…
neural-networks
deep-learning
gpu
cuda
autograd
python3
automatic-differentiation
reinforcement-learning
Python
Updated Apr 4, 2019
Source code for Deep Multigrid method https://arxiv.org/pdf/1711.03825.pdf
Jupyter Notebook
Updated Mar 24, 2019
a simple implementation of autograd engine
Jupyter Notebook
Updated Sep 22, 2018
A set of autograd tutorial notebooks
autograd
autograd-tutorials
jupyter-notebook
lecture-notes
automatic-differentiation
backpropagation
Jupyter Notebook
Updated Feb 8, 2019
Machine Learning models for large datasets
big-data
large-dataset
bigml
guinea-pig
lda
hadoop
autodiff
parameter-server
lda-gibbs-sampling
guineapig
sparse-sgd
autograd
document-classification
mapreduce
hadoop-mapreduce
Gnuplot
Updated Jan 19, 2018
Autograd compatible Givens Transforms which is especially useful for optimization on a Stiefel Manifold.
Python
Updated Apr 3, 2018
An implementation of simple deep learning framework with autograd, from scratch (numpy)
Python
Updated Mar 16, 2019
Deep Learning for Swift - An implementation of automatic differentiation and various deep learning operators
deep-learning
neural-networks
autograd
automatic-differentiation
gradient-descent
recurrent-neural-networks
lstm
gated-recurrent-unit
Swift
Updated Mar 31, 2019
Computation graphs, automatic differentiation and machine learning for Kotlin
Kotlin
Updated Feb 24, 2019
Examples from scratch using PyTorch
Jupyter Notebook
Updated Nov 1, 2018