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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

tensorViz helps developers explore PyTorch models and JAX/Flax programs as interactive graphs. For PyTorch, users can expand nested modules, inspect tensor shapes captured from one forward pass, jump to Python source, and review architecture changes beside code diffs. The website offers recorded model graphs to explore without installation. The free VS Code extension is available from the Visual Studio Marketplace and Open VSX. Local capture requires Python, model dependencies, and example inputs. Standalone coding-agent plugins are an Apple Silicon macOS preview; MCP agents can also connect to the extension. JAX/Flax graphs use CPU tracing with inferred shapes, and PyTorch source edits are unavailable for them.

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 Supported
Mac Supported
Linux 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

Machine learning engineers, PyTorch developers, researchers and students exploring model architecture, tensor shapes and architecture changes.

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 Supported

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

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

Pricing

$0
The VS Code extension is free to install. Core graph exploration and source-edit forms work without an agent or provider API key; connecting a coding agent is optional.
Free Version 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:

Review this Software

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

tensorViz
tensorviz.dev/

Alternatives

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Deep Learning Supported
Neural Network Supported

Categories

Deep Learning Supported
Machine Learning 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

Cameralyze Supported
Codex CLI Not Supported
Comet LLM Supported
Dataiku Supported
Flower Supported
GitHub Not Supported
Lambda Supported
MLReef Supported
MLflow Supported
Model Context Protocol (MCP) Not Supported
RazorThink Supported
RunCode Supported
Spell Supported
StreamFlux Supported
Superwise Supported
TensorFlow Supported
Thunder Compute Supported
Vectice Supported

Integrations

Cameralyze Not Supported
Codex CLI Supported
Comet LLM Not Supported
Dataiku Not Supported
Flower Not Supported
GitHub Supported
Lambda Not Supported
MLReef Not Supported
MLflow Not Supported
Model Context Protocol (MCP) Supported
RazorThink Not Supported
RunCode Not Supported
Spell Not Supported
StreamFlux Not Supported
Superwise Not Supported
TensorFlow Not Supported
Thunder Compute Not Supported
Vectice Not Supported
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