Hands-on Machine Learning with JavaScript

Bring the power of neural networks to create intelligent web applications

Key Features

• Solve complex computational problems in browser with your favourite JavaScript;
• Teach your browser how to using the power of machine learning;
• Get thorough understanding of the insightful discoveries on Web interface and programmatic API's of the rapidly developing world of machine learning.

Book Description

JavaScript has pushed 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 just makes your browsers smarter than ever before with the ability to learn patterns and reproduce them to become a part of innovative products and applications.

This book presents various avenues of Machine Learning in a practical and objective way and implementing them using the JavaScript language. Predicting behaviors, analyzing feelings, grouping data, building neural models, are some of the skills you will gain from this book. With 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. You will also learn how to work with deep neural networks and teach your application to gain insights from data. You will gain practical hands-on evaluating and implementing the right model as per your use.

By the end of this book, you will learn to implement different JS libraries such as naturalnode, brain, harthur, classifier, and much more to design smarter applications for your business.

What you will learn

• Get a complete overview of how JavaScript can be used for machine learning
• Learn pre-processing of data with operations like handling, cleaning, and preparation
• Explore mining and pattern extraction with JavaScript
• Build your own model for classification, clustering, and prediction
• Understand which model is most appropriate for each type of problem
• Apply machine learning techniques in real world applications
• Learn how JavaScript can be a powerful language for machine learning

Who This Book Is For

This book appeals to data scientists, machine learning practitioners and JavaScript developers who want to implement machine learning to make their applications smarter and gain insightful information from the data. JavaScript developers who wish to enter the field of machine learning without switching to another language will also find this book quite useful. Working knowledge of JavaScript language is expected to get the most out of the book.

Burak Kanber is an entrepreneur, software engineer, and the co-author of "Genetic Algorithms in Java". He earned his Bachelor's and Master's degrees in Mechanical Engineering from the prestigious Cooper Union in New York City, where he concentrated on software modeling and simulation of hybrid vehicle powertrains.

Currently, Burak is a founder and the CTO of Tidal Labs, a popular enterprise influencer marketing platform. Previously, Burak had founded several startups, most notably a boutique design and engineering firm that helped startups and small businesses solve difficult technical problems. Through Tidal Labs, his engineering firm, and his other consulting work, Burak has helped design and produce dozens of successful products and has served as a technical advisor to many startups.

Burak's core competencies are in machine learning, web technologies (specifically PHP and JavaScript), engineering (software, hybrid vehicles, control systems), product design and agile development. He's also worked on several interactive art projects, is a musician, and is a published engineer.