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Algorithms of the Intelligent Web by Douglas G. McIlwraith
£35.99
Available
Product Ref. (e.g. ISBN, SKU)
9781617292583
Published:
19 Sep 2016
Format:
Paperback
Number of pages:
240 pages
Dimensions:
235x187x10mm
Weight:
0.430kgs
Author:
The second edition of 'Algorithms of the Intelligent Web' has been totally revised and teaches the most important approaches to algorithmic web data analysis, enabling readers to create machine learning applications that crunch, munge, and wrangle data collected from users, web applications, sensors, and website logs. Key machine learning concepts are explained and introduced with many code examples in Python's scikit-learn.
Summary
Algorithms of the Intelligent Web, Second Edition teaches the most important approaches to algorithmic web data analysis, enabling you to create your own machine learning applications that crunch, munge, and wrangle data collected from users, web applications, sensors and website logs.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
Valuable insights are buried in the tracks web users leave as they navigate pages and applications. You can uncover them by using intelligent algorithms like the ones that have earned Facebook, Google, and Twitter a place among the giants of web data pattern extraction.
About the Book
Algorithms of the Intelligent Web, Second Edition teaches you how to create machine learning applications that crunch and wrangle data collected from users, web applications, and website logs. In this totally revised edition, you'll look at intelligent algorithms that extract real value from data. Key machine learning concepts are explained with code examples in Python's scikit-learn. This book guides you through algorithms to capture, store, and structure data streams coming from the web. You'll explore recommendation engines and dive into classification via statistical algorithms, neural networks, and deep learning.
What's Inside
Introduction to machine learningExtracting structure from dataDeep learning and neural networksHow recommendation engines work
About the Reader
Knowledge of Python is assumed.
About the Authors
Douglas McIlwraith is a machine learning expert and data science practitioner in the field of online advertising. Dr. Haralambos Marmanis is a pioneer in the adoption of machine learning techniques for industrial solutions. Dmitry Babenko designs applications for banking, insurance, and supply-chain management. Foreword by Yike Guo.
Table of Contents
Building applications for the intelligent webExtracting structure from data: clustering and transforming your data Recommending relevant contentClassification: placing things where they belongCase study: click prediction for online advertisingDeep learning and neural networksMaking the right choiceThe future of the intelligent webAppendix - Capturing data on the web
About the Author: Douglas McIlwraith earned his first degree at Cambridge in computer science before completing a PhD in sensor fusion from Imperial College in London. He is a machine learning expert, currently working as senior data scientist for a London-based advertising company.
| Number of pages | 240 |
|---|
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