Mcllwraith Douglas G., Marmanis Haralambos, Babenko Dmitry. Algorithms of the Intelligent Web

2nd Edition. — Manning, 2016. — 325 p. — ISBN: 978-1617292583.There’s priceless insight trapped in the flood of data users leave behind as they interact with web pages and applications. Those insights can be unlocked by using intelligent algorithms like the ones that have earned Facebook, Google, Twitter, and Microsoft a place among the giants of web data pattern extraction. Improved search, data classification, and other smart pattern matching techniques can give an enormous advantage to understanding and interacting with users. Algorithms of the Intelligent Web, Second Edition 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. The book guides readers through the underlying machinery and intelligent algorithms to capture, store, and structure data streams. Readers will explore recommendation engines from the example of Netflix movie recommendations and dive into classification via statistical algorithms, neural networks, and deep learning. They will also consider the ins and outs of ranking and how to test applications based on intelligent algorithms.Building applications for the intelligent web
Extracting structure from data: clustering and transforming your data
Recommending relevant content
Classification: placing things where they belong
Case study: click prediction for online advertising
Deep learning and neural networks
Making the right choice
The future of the intelligent web
Capturing data on the web