deeplearn.js alternatives and similar libraries

Based on the "Machine Learning" category.
Alternatively, view deeplearn.js alternatives based on common mentions on social networks and blogs.

Tesseract.js

9.4 7.7 L3 deeplearn.js VS Tesseract.js

Pure Javascript OCR for more than 100 Languages 📖🎉🖥
ConvNetJS

8.4 0.0 L3 deeplearn.js VS ConvNetJS

Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.

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natural

7.8 5.7 L5 deeplearn.js VS natural

general natural language facilities for node
Brain.js

7.5 0.0 L5 deeplearn.js VS Brain.js

[UNMAINTAINED] Simple feed-forward neural network in JavaScript
Synaptic.js

7.0 0.0 L2 deeplearn.js VS Synaptic.js

architecture-free neural network library for node.js and the browser
Keras.js

6.3 0.0 deeplearn.js VS Keras.js

Run Keras models in the browser, with GPU support using WebGL
neurojs

6.0 0.0 deeplearn.js VS neurojs

A JavaScript deep learning and reinforcement learning library.
Propel

4.7 0.0 deeplearn.js VS Propel

Differential Programming in JavaScript.
ml.js

4.7 2.4 deeplearn.js VS ml.js

Machine learning tools in JavaScript
m2cgen

4.6 7.2 deeplearn.js VS m2cgen

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
WebDNN

4.3 5.0 deeplearn.js VS WebDNN

The Fastest DNN Running Framework on Web Browser
Mind.js

3.9 1.6 L4 deeplearn.js VS Mind.js

A neural network library built in JavaScript
Limdu.js

3.4 2.6 L4 deeplearn.js VS Limdu.js

Machine-learning for Node.js
DN2A

2.5 0.0 L5 deeplearn.js VS DN2A

DN2A - Digital Neural Networks Architecture
Dannjs

2.2 6.7 deeplearn.js VS Dannjs

Easy to use Deep Neural Network Library for JavaScript.
Synapses

1.1 0.0 deeplearn.js VS Synapses

A group of neural-network libraries for functional and mainstream languages
ml5.js

- deeplearn.js VS ml5.js

Friendly Machine Learning for the Web.
TensorFlow.js

- deeplearn.js VS TensorFlow.js

A JavaScript library for training and deploying ML models in the browser and on Node.js.