Endless possibilities as a javascript developer
Most machine-learning applications these days use R or Python. But JavaScript has a great future as a machine learning language.
Some of the advantages of using JavaScript for machine learning are:
- JavaScript Everywhere. You can stick with javascript for the UI part as well as for the ML part.
2. JavaScript outperforms Python in terms of speed.
3. We can make full use of GPU with javascript and WebGL
Here are the top AI ML libraries for JavaScript:
1. TensorFlow
TensorFlow is an end-to-end open-source machine learning platform and a JavaScript library for training and deploying deep learning models in the browser and NodeJS.
2. BrainJS
BrainJS is a JavaScript-written, GPU-accelerated library of neural networks. It is released as free and open-source software under the MIT License. It can be used in both the browser and Node.js backends.
3. Mind
Mind is a flexible JavaScript-based neural network library for NodeJS and browsers. This library makes use of a matrix implementation to efficiently process training data.
4. stdlib
Short for Standard Lib, stdlib is a standard library for JavaScript and Node.js that offers a range of numerical and scientific calculation capabilities for your Machine Learning applications.
5. Deeplearnjs
The deeplearn library supports hardware acceleration and comes equipped with all the building blocks required for training and running pre-trained Machine Learning models in your browser
6. ConvNetJS
A JavaScript Machine Learning library for training your Deep Learning models entirely from your browser. Apart from supporting browsers, the library also supports Node.js.
Learning one language for doing ML as well as creating UI can really be an advantage and JavaScript is a clean bet for that
Thanks for reading this blog. You can dig deeper to see some of the best machine-learning solutions in Javascript
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