Software Alternatives, Accelerators & Startups

ConvNetJS

ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in a browser.

Some of the top features or benefits of ConvNetJS are: Ease of Use, Interactive Demos, Visualization, and No Dependencies. You can visit the info page to learn more.

ConvNetJS

ConvNetJS Alternatives & Competitors

The best ConvNetJS alternatives based on verified products, community votes, reviews and other factors.
Filter: 7 Open-Source Alternatives. Latest update:

  1. 12

    Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

    Key Keras features:

    User-Friendly Modularity Pre-trained Models Integration with TensorFlow

    Open Source

    /keras-alternatives
  2. 10

    TFlearn is a modular and transparent deep learning library built on top of Tensorflow.

    Key TFlearn features:

    User-Friendly Interface Modular Design Integration with TensorFlow Pre-built Models

    Open Source

    /tflearn-alternatives
  3. Consent-Based Identification of the Person Visiting Your Website Including First Name, Last Name, Email & 37 Other Data Points. Identify and Influence Your Engaged Website Visitors into Sales-Ready Leads – Before You Commit a Single Working Hour.

    Key VisualVisitor features:

    AI Sales Rep WebID +Person (B2C) WebID +Employee (B2B) Who To Contact - Contact Database (B2B)

    Try for free paid Free Trial $299.0 / Monthly (WebID Includes 1,000 Identifications )

    Try for free
  4. The World's AI.

    Key Clarifai features:

    API Artificial Intelligence Workflow Management Workflow Automation

    freemium

    /clarifai-alternatives
  5. 11

    Machine Learning.

    Key Microsoft Cognitive Toolkit (Formerly CNTK) features:

    Efficiency Scalability Flexibility Seamless Integration

    /microsoft-cognitive-toolkit-formerly-cntk-alternatives
  6. 10

    Knet is a deep learning framework that supports GPU operation and automatic differentiation using dynamic computational graphs for models.

    Key Knet features:

    Efficiency Flexibility Julia Integration Community and Support

    /knet-alternatives
  7. 10

    Merlin is a deep learning framework written in Julia, it aims to provide a fast, flexible and compact deep learning library for machine learning.

    Key Merlin features:

    Julia Language Integration Composable Machine Learning Models Interoperability Community Support

    /merlin-alternatives
  8. 10

    DeepPy is a MIT licensed deep learning framework that tries to add a touch of zen to deep learning as it allows for Pythonic programming.

    Key DeepPy features:

    Ease of Use Python Integration Lightweight

    /deeppy-alternatives
  9. 10

    Chainer is a flexible and intuitive framework for Neural Networks.

    Open Source

    /chainer-alternatives
  10. Swift Brain is a neural network / machine learning library written in Swift for AI algorithms.

    Key Swift Brain features:

    Ease of Use Integration with Swift Lightweight Open Source

    /swift-brain-alternatives
  11. See sharks everywhere with this AR app 🦈.

    Key SHARK features:

    Versatility Modular Design Performance Open Source

    /shark-alternatives
  12. Artificial intelligence and machine learning library written in Swift.

    Key Swift AI features:

    Native Swift Integration Open Source Performance Optimizations Community Support

    /swift-ai-alternatives
  13. BrainCore is a simple but fast neural network framework written in Swift.

    Open Source

    /braincore-alternatives
  14. MLKit is a simple machine learning framework written in Swift.

    Key MLKit features:

    Feature-Rich Ease of Integration Regular Updates Open-Source

    Open Source

    /mlkit-alternatives
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