Book Image

Hands-on Machine Learning with JavaScript

Book Image

Hands-on Machine Learning with JavaScript

Overview of this book

In over 20 years of existence, JavaScript has been pushing beyond the boundaries of web evolution with proven existence on servers, embedded devices, Smart TVs, IoT, Smart Cars, and more. Today, with the added advantage of machine learning research and support for JS libraries, JavaScript makes your browsers smarter than ever with the ability to learn patterns and reproduce them to become a part of innovative products and applications. Hands-on Machine Learning with JavaScript presents various avenues of machine learning in a practical and objective way, and helps implement them using the JavaScript language. Predicting behaviors, analyzing feelings, grouping data, and building neural models are some of the skills you will build from this book. You will learn how to train your machine learning models and work with different kinds of data. During this journey, you will come across use cases such as face detection, spam filtering, recommendation systems, character recognition, and more. Moreover, you will learn how to work with deep neural networks and guide your applications to gain insights from data. By the end of this book, you'll have gained hands-on knowledge on evaluating and implementing the right model, along with choosing from different JS libraries, such as NaturalNode, brain, harthur, classifier, and many more to design smarter applications.
Table of Contents (14 chapters)

Summary

In this chapter, you learned a number of techniques used in forecasting, signal processing, regression, and time-series data analysis. Because forecasting and time-series analysis is a broad category, there is no single algorithm you can use that covers every case. Instead, this chapter has given you an initial toolbox of important concepts and algorithms that you can start applying to your forecasting and regression tasks.

Specifically, you learned about the difference between regression and classification. While classification assigns labels to data points, regression attempts to predict the numerical value of a data point. Not all regression is necessarily forecasting, but regression is the single most significant technique used in forecasting.

After learning the basics of regression, we explored a few specific types of regression. Namely, we discussed linear, polynomial...