Hands-on Machine Learning with JavaScript: Solve complex computational web problems using machine learning
By 作者: Burak Kanber
ISBN-10 书号: 1788998243
ISBN-13 书号: 9781788998246
Release Finelybook 出版日期: 2018-05-29
pages 页数: (356 )

$44.99


Book Description to Finelybook sorting

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.

Contents
1: EXPLORING THE POTENTIAL OF JAVASCRIPT
2: DATA EXPLORATION
3: TOUR OF MACHINE LEARNING ALGORITHMS
4: GROUPING WITH CLUSTERING ALGORITHMS
5: CLASSIFICATION ALGORITHMS
6: ASSOCIATION RULE ALGORITHMS
7: FORECASTING WITH REGRESSION ALGORITHMS
8: ARTIFICIAL NEURAL NETWORK ALGORITHMS
9: DEEP NEURAL NETWORKS
10: NATURAL LANGUAGE PROCESSING IN PRACTICE
11: USING MACHINE LEARNING IN REAL-TIME APPLICATIONS
12: CHOOSING THE BEST ALGORITHM FOR YOUR APPLICATION
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
Authors
Burak Kanber
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.

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