Machine learning in JavaScript

The web is the most accessible platform and JavaScript is the language used across the web, hence ML in JavaScript gives us more control and accessibility. In the Why you need Danfo.js section of Chapter 3, Getting Started with Danfo.js, we talked about the importance of bringing ML the web. We also talked about how browsers' computational power is increasing and how this is a benefit to JavaScript for ML.

In this section, I will list some open source tools for ML tasks in the browser:

• TensorFlow.js (tfjs) (https://github.com/tensorflow/tfjs): A WebGL accelerated JavaScript library for training and deploying ML models.
• datacook (https://github.com/imgcook/datacook): A JavaScript framework for feature engineering on datasets.
• Nlp.js (https://github.com/axa-group/nlp.js): A JavaScript framework for NLP tasks such as sentiment analysis, automatic language identity, entity extraction, and so on.
• Natural (https://github.com/NaturalNode...