
Machine Learning with JavaScript
Joao Oliveira(Author)
Packt Publishing
Published on 29. December 2017
Book
Paperback/Softback
345 pages
978-1-78728-019-9 (ISBN)
Description
A definitive guide to creating intelligent web applications with the best of machine learning and javascript
About This Book
* Solve complex computational problems in browser with your favourite JavaScript.
* Teach your browser how to learn from rules using the power of machine learning.
* Get thorough understanding of the insightful discoveries on Web interface and programmatic API's of the rapidly developing frontend or backend javascript world of machine learning.
Who This Book Is For
This book appeals to JavaScript developers who want to make their JavaScript 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.
What You Will Learn
* Overview of the state of the art of machine learning
* Pre-processing of data: handling, cleaning, and preparation
* Mining and Pattern Extraction with Javascript
* Build your own model for classification, clustering, or prediction
* Understand which model is most appropriate for each type of problem
* Apply machine learning techniques in real world applications
* Understand how Javascript can be a powerful language for machine learning
In Detail
Over 20 years of existence, JavaScript has pushed beyond the boundaries of web evolution with proven existence on servers, embedded devices, Smart TVs, IoT, Smart Cars,etc. 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. Through the course of the 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.
By the end of this book, you'll gained practical hands-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 for your business.
About This Book
* Solve complex computational problems in browser with your favourite JavaScript.
* Teach your browser how to learn from rules using the power of machine learning.
* Get thorough understanding of the insightful discoveries on Web interface and programmatic API's of the rapidly developing frontend or backend javascript world of machine learning.
Who This Book Is For
This book appeals to JavaScript developers who want to make their JavaScript 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.
What You Will Learn
* Overview of the state of the art of machine learning
* Pre-processing of data: handling, cleaning, and preparation
* Mining and Pattern Extraction with Javascript
* Build your own model for classification, clustering, or prediction
* Understand which model is most appropriate for each type of problem
* Apply machine learning techniques in real world applications
* Understand how Javascript can be a powerful language for machine learning
In Detail
Over 20 years of existence, JavaScript has pushed beyond the boundaries of web evolution with proven existence on servers, embedded devices, Smart TVs, IoT, Smart Cars,etc. 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. Through the course of the 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.
By the end of this book, you'll gained practical hands-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 for your business.
More details
Language
English
Place of publication
Birmingham
United Kingdom
Dimensions
Height: 235 mm
Width: 191 mm
ISBN-13
978-1-78728-019-9 (9781787280199)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Joao Gabriel Rodrigues de Oliveira is a computer engineer and has a master in computer science. He is affiliated with the Federal University of Para. Being a University Professor and Ph.D. candidate, he is focused on the construction of a computational model for machine learning in the context of BigData. Over more than 10 years working with technology, he added a transversal knowledge working in several areas. He has collaborated in projects in important research institutes, such as MAREI - Center for Marine and Renewable Energy and LINC - Laboratory of Computational Intelligence and Operational Research.
An author of several scientific articles in the field of data mining and computational intelligence, he has a patent deposit of invention, where he proposes a new architecture for the clustering of large volumes of data in real time.
He is currently a data science consultant and is a member of Epitrack's board of data scientists where they use computing models to combat epidemics based on digital disease detection and participatory surveillance.
An author of several scientific articles in the field of data mining and computational intelligence, he has a patent deposit of invention, where he proposes a new architecture for the clustering of large volumes of data in real time.
He is currently a data science consultant and is a member of Epitrack's board of data scientists where they use computing models to combat epidemics based on digital disease detection and participatory surveillance.