Node.js Projects

Chapter 7. Natural Language Processor Sentiment Analysis

This chapter covers the following:

• Processing text using machine learning–powered libraries

• Wrapping a machine learning model in a Node service

• Building an interactive command-line app

In this chapter, you’ll build a sentiment analysis app using Node and natural language processing (NLP) techniques to interpret emotional tone from everyday text and gain practical experience working with machine learning (ML) in JavaScript.

Through these techniques you’ll learn the ways of an ML engineer and build your own ML-driven Node app. ML has been growing in importance through its use in technology in just about every industry. As a subset of artificial intelligence (AI), ML teams from startups to enterprise companies are racing to deliver an experience that most closely mimics what you’d expect from a human expert. If you’re new to ML, then all you need to know is that a lot of math and statistics are performed on data from the real world to provide you with a JavaScript function that can take an input and offer a result, such as a sentiment score, based on patterns learned during training on labeled datasets. If you are familiar with how ML works, then it’s likely you’ve learned about the various models in use today. An ML model is what data scientists will train in order to build a function that generalizes well to new, unseen inputs.

From helping predict your next purchase, to movie recommendations and facial recognition, ...