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About

Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API.

About

GPUs bring data in and out quickly, but have little locality of reference because of their small caches. They are geared towards applying a lot of compute to little data, not little compute to a lot of data. The networks designed to run on them therefore execute full layer after full layer in order to saturate their computational pipeline (see Figure 1 below). In order to deal with large models, given their small memory size (tens of gigabytes), GPUs are grouped together and models are distributed across them, creating a complex and painful software stack, complicated by the need to deal with many levels of communication and synchronization among separate machines. CPUs, on the other hand, have large, much faster caches than GPUs, and have an abundance of memory (terabytes). A typical CPU server can have memory equivalent to tens or even hundreds of GPUs. CPUs are perfect for a brain-like ML world in which parts of an extremely large network are executed piecemeal, as needed.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Not Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers interested in an deep learning API solution to minimize the number of user actions required for common use cases

Audience

Companies doing AI and ML development

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5

Reviews/Ratings

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

This software hasn't been reviewed yet. Be the first to provide a review:

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Pros & Cons from Real Users

Pros

  • I mostly code in Python, so using Keras for my deep learning needs wasn't too hard to get used to, given the abundance of documentation and ease of writing modular code with its API.

Cons

  • Keras only has high level APIs, unlike Tensorflow, which has both high and low level support.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Keras
United States
keras.io

Company Information

Neural Magic
Founded: 2018
United States
neuralmagic.com

Alternatives

Alternatives

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Neural Designer

Artelnics

Categories

Deep Learning Supported
Neural Network Supported

Categories

Deep Learning Supported
Machine Learning Supported
Neural Network Supported

Deep Learning Features

Convolutional Neural Networks Supported
Document Classification Not Supported
Image Segmentation Not Supported
ML Algorithm Library Not Supported
Model Training Not Supported
Neural Network Modeling Not Supported
Self-Learning Not Supported
Visualization Supported

Integrations

Akira AI Supported
AutoKeras Supported
BentoML Supported
Comet Supported
Gemma 3n Supported
Gemma 4 Supported
Gradient Supported
Graphcore Supported
JAX Supported
Jovian Supported
MLReef Supported
MLflow Supported
OpenVINO Supported
Polyaxon Supported
RunCode Supported
StreamFlux Supported
Superwise Supported
TensorFlow Supported
Thunder Compute Supported

Integrations

Akira AI Not Supported
AutoKeras Not Supported
BentoML Not Supported
Comet Not Supported
Gemma 3n Not Supported
Gemma 4 Not Supported
Gradient Not Supported
Graphcore Not Supported
JAX Not Supported
Jovian Not Supported
MLReef Not Supported
MLflow Not Supported
OpenVINO Not Supported
Polyaxon Not Supported
RunCode Not Supported
StreamFlux Not Supported
Superwise Not Supported
TensorFlow Not Supported
Thunder Compute Not Supported
Claim Keras and update features and information
Claim Keras and update features and information
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