Hands-on Machine Learning with JavaScript: Solve complex computational web problems using machine learning

Hands-on Machine Learning with JavaScript: Solve complex computational web problems using machine learningReviews
Author: Burak Kanber
Pub Date: 2018
ISBN: 978-1788998246
Pages: 356
Language: English
Format: PDF/EPUB
Size: 30 Mb

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A definitive guide to creating an intelligent web application with the best of machine learning and JavaScript
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.
What you will learn

  • Get an overview of state-of-the-art machine learning
  • Understand the pre-processing of data handling, cleaning, and preparation
  • Learn Mining and Pattern Extraction with JavaScript
  • Build your own model for classification, clustering, and prediction
  • Identify the most appropriate model for each type of problem
  • Apply machine learning techniques to real-world applications
  • Learn how JavaScript can be a powerful language for machine learning