About

A powerful, flexible, and intuitive framework for neural networks. Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort. Chainer supports various network architectures including feed-forward nets, convnets, recurrent nets and recursive nets. It also supports per-batch architectures. Forward computation can include any control flow statements of Python without lacking the ability of backpropagation. It makes code intuitive and easy to debug. Comes with ChainerRLA, a library that implements various state-of-the-art deep reinforcement algorithms. Also, with ChainerCVA, a collection of tools to train and run neural networks for computer vision tasks. Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort.

About

The Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers. CNTK can be included as a library in your Python, C#, or C++ programs, or used as a standalone machine-learning tool through its own model description language (BrainScript). In addition you can use the CNTK model evaluation functionality from your Java programs. CNTK supports 64-bit Linux or 64-bit Windows operating systems. To install you can either choose pre-compiled binary packages, or compile the toolkit from the source provided in GitHub.

About

Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.

About

The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Researchers, developers, and anyone looking for an intuitive framework solution designed for neural networks

Audience

Developers and enterprises seeking a toolkit solution designed for commercial-grade distributed deep learning

Audience

Component Library solution for DevOps teams

Audience

Developers interested in a beautiful but advanced programming language

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 4.3 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Chainer
Japan
chainer.org

Company Information

Microsoft
Founded: 1975
United States
docs.microsoft.com/en-us/cognitive-toolkit/

Company Information

NumPy
numpy.org

Company Information

Python
Founded: 1991
www.python.org

Alternatives

Alternatives

Alternatives

Alternatives

h5py

h5py

HDF5
Neural Designer

Neural Designer

Artelnics
MXNet

MXNet

The Apache Software Foundation

Categories

Categories

Categories

Categories

Deep Learning Features

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Integrations

Backslash Security
Boofuzz
Codacy
Codeaid
Databricks Data Intelligence Platform
ERNIE X1.1
Eventarc
Feast
GPT-4.1
Gemini-Exp-1206
MERCI Cloud ERP
Meya
MosaicML
NVIDIA DeepStream SDK
SX.ORG
Safurai
Smolagents
Superblocks
Tarpaulin
scikit-learn

Integrations

Backslash Security
Boofuzz
Codacy
Codeaid
Databricks Data Intelligence Platform
ERNIE X1.1
Eventarc
Feast
GPT-4.1
Gemini-Exp-1206
MERCI Cloud ERP
Meya
MosaicML
NVIDIA DeepStream SDK
SX.ORG
Safurai
Smolagents
Superblocks
Tarpaulin
scikit-learn

Integrations

Backslash Security
Boofuzz
Codacy
Codeaid
Databricks Data Intelligence Platform
ERNIE X1.1
Eventarc
Feast
GPT-4.1
Gemini-Exp-1206
MERCI Cloud ERP
Meya
MosaicML
NVIDIA DeepStream SDK
SX.ORG
Safurai
Smolagents
Superblocks
Tarpaulin
scikit-learn

Integrations

Backslash Security
Boofuzz
Codacy
Codeaid
Databricks Data Intelligence Platform
ERNIE X1.1
Eventarc
Feast
GPT-4.1
Gemini-Exp-1206
MERCI Cloud ERP
Meya
MosaicML
NVIDIA DeepStream SDK
SX.ORG
Safurai
Smolagents
Superblocks
Tarpaulin
scikit-learn
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