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Hands-on Machine Learning with JavaScript

 

Hands-on Machine Learning with JavaScript

Autor: Burak Kanber
Broj strana: 356
ISBN broj: 9781788998246
Izdavač: PACKT PUBLISHING
Godina izdanja: 2018.

Pregleda (30 dana / ukupno): 42 / 151

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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

Book Description

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.

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.

Table of Contents

Chapter 1: Exploring the Potential of JavaScript
Chapter 2: Data Exploration
Chapter 3: Tour of Machine Learning Algorithms
Chapter 4: Grouping with Clustering Algorithms
Chapter 5: Classification Algorithms
Chapter 6: Association Rule Algorithms
Chapter 7: Forecasting with Regression Algorithms
Chapter 8: Artificial Neural Network Algorithms
Chapter 9: Deep Neural Networks
Chapter 10: Natural Language Processing in Practice
Chapter 11: Using Machine Learning in Real-Time Applications
Chapter 12: Choosing the Best Algorithm for Your Application

 

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