AI (Artificial Intelligence) has been the buzzword of this decade. It is the technology to give a machine or program the ability to copy human cognition or simply, to solve problems on its own. Programs that implement AI algorithms require high efficiency and optimiza
Machine Learning models are no more just desktop-based. With the advancement of the web, there are now several rich libraries that can be used to produce models, train those and visualize output in the browser. Both machine learning and deep learning models can be produced in JavaScript, PHP and Ruby.
These libraries have heavily contributed to bringing Machine Learning on the web:
1. TensorFlow.js:
Managed by Google, it is a reputed JavaScript library to produce & train machine learning models in JavaScript and run in the browser. Models written in Python TensorFlow can be converted to JavaScript using TensorFlow.js .
Official Website: https://TensorFlow.org/js
2. RubixML:
PHP has been present on the web since almost the beginning. RubixML is a high-level open-source library to produce machine learning models using PHP. It comes with support for more than 40 different machine learning and deep learning algorithms written in PHP.
Official Website: https://Rubixml.com
3. Rumale:
A Ruby library for machine learning, it is similar to Python Scikit-Learn in interface. It has support for a wide range of algorithms.
Official Website: https://github.com/yoshoku/rumale
4. PHP-ML:
Another open-source library, machine learning models can be developed in PHP using PHP-ML. If you want to perform Data Mining and Data Analysis in PHP, PHP-ML is your choice. This library requires no additional dependencies.
Official Website: https://php-ml.org
5. BrainJS:
It is a JavaScript library that uses GPU to compute fast and return output in plain JavaScript. This is more suitable to work with neural networks.
Official Website: https://Brain.js.org
Any developer may contribute to improve these open-source libraries and keep AI ever-green on web.
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