One of the new additions to TensorFlow in the last months has been the eager execution, an additional low-level interface promising to…
Now you can develop deep learning applications with Google Colaboratory -on the free Tesla K80 GPU- using Keras, Tensorflow and PyTorch.
PyTorch is a python package that provides two high-level features: Tensor computation (like numpy) with strong GPU acceleration Deep Neural Networks built on a tape-based autograd system
PyCUDA gives you easy, Pythonic access to Nvidia’s CUDA parallel computation API.
PyCUDA is a great library if you want to use gpu computing with NVIDIA chips. If you want a more portable approach or if you have ATI chips instead of NVIDIA, then you might consider PyOpenCl instea
Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to
One of Theano’s design goals is to specify computations at an abstract level, so that the internal function compiler has a lot of flexibility about how to carry out those computations. One of the ways we take advantage of this flexibility is in carrying out calculations on a graphics card.
At Facebook, research permeates everything we do. We believe the most interesting research questions are derived from real world problems.
unet for image segmentation
pix2pix is shorthand for an implementation of a generic image-to-image translation using conditional adversarial networks, originally introduced by Phillip Isola et al.
faster-rcnn.pytorch - A faster pytorch implementation of faster r-cnn
NumbaPro was one of the early tools that could compile Python for execution on NVIDIA GPUs. Our goal with NumbaPro was to make cutting-edge GPUs more accessible to Python users, and to improve the performance of numerical code in Python.
Pyculib is a package that provides access to several numerical libraries that are optimized for performance on NVidia GPUs.
Python is one of the most popular programming languages today for science, engineering, data analytics and deep learning applications. However, as an interpreted language, it has been considered too slow for high-performance computing. That has changed with CUDA Python from Continuum Analytics.
estool - Evolution Strategies Tool
A Python implementation of CMA-ES and a few related numerical optimization tools. The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a stochastic derivative-free numerical optimization algorithm for difficult (non-convex, ill-conditioned, multi-modal, rugged, noisy) optimization problems in continuous search spaces.
Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator.
ray - A high-performance distributed execution engine
golearn - Machine Learning for Go
Go is a lovely little programming language designed by smart people you can trust and continuously improved by a large and growing open-source community.
New from Google. Kind of "Machine Learning for dummies".
A list of the 10 best AI and ML tools for developers.
Open source is the best choice for Machine Learning, due to its support communities and wide offer of specific libraries. And of course, they are free.