Algorithms of the Intelligent Web.pdf

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MEAP Edition

Manning Early Access Program

Algorithms of the Intelligent Web

Second Edition

Version 9

For more information on this and other Manning titles go to

www.manning.com

https://forums.manning.com/forums/algorithms-of-the-intelligent-web-second-edition

welcome

Thank you for purchasing the MEAP edition of Algorithms of the

Intelligent Web, Second

Edition.

Intelligent Algorithms are a very hot topic right now and some of this interest can be

placed at the doors of the giants of the web. Google, Facebook, LinkedIn and many others

have all openly discussed their research to better deal with the vast quantities of data

generated by their users, and to use this data to better target messages towards you, the

reader of this book!

While much of this research is open to the public, it can often seem difficult to get started

in this complex area. The development of intelligent algorithms sits at the intersection of

several disciplines and the practitioner is often well versed in databases and data systems,

statistics and machine learning. Conscious that this it is difficult to obtain this level of

exposure without being immersed in the field, we decided to rewrite Algorithms of the

Intelligent Web with this in mind.

In these chapters you will find many of the core algorithms used to make real-time

decisions on the web. Concepts are introduced in plain English and illustrated with Python’s

scikit learn. We’ll navigate a host of algorithms together and provide you with the basic

mathematics to illuminate them, without drowning in Greek symbols.

We hope you that you enjoy the second edition of

Algorithms of the Intelligent Web

and

that it will occupy an important place on your digital (and physical!) bookshelf.

We also encourage you to post any questions or comments you have about the content in

the book’s forum. We appreciate knowing where we can make improvements and increase

your understanding of the material.

—Dr Douglas McIlwraith

brief contents

1 Building applications for the intelligent web

2 Extracting structure from data: clustering and transforming your data

3 Recommending relevant content

4 Classification: placing things where they belong

5 Case study: click prediction for online advertising

6 Deep learning and neural networks

7 Making the right choice

8 The future of the intelligent web

PPENDIXES

A Capturing Data on the Web

Building applications for the

intelligent web

This chapter covers



Recognizing intelligence on the web

Types of intelligent algorithms

Evaluating intelligent algorithms

The

intelligent web

means different things to different people. To some it represents the

evolution of the web into a more responsive and useful entity that can learn from and react to

its users. To others it represents the inclusion of the web into many more aspects of our lives.

To me, far from being the first iteration of Skynet, in which computers take over in a

dystopian future, the intelligent web is about designing and implementing more naturally

responsive applications that make our online experiences better in some quantifiable way.

There’s a good chance that every reader has encountered machine intelligence on many

separate occasions, and this chapter will highlight some examples so that you’ll be better

equipped to recognize these in the future. This will, in turn, help you understand what’s really

happening under the hood when you interact with intelligent applications again.

Now that you know this book isn’t about writing entities that will try to take over the world,

we should perhaps discuss some other things that you won’t find within these pages! First,

this is very much a back-end book. In these pages, you won’t learn about beautiful interactive

other simple mistakes. These will be cleaned up during production of the book by copyeditors and proofreaders.

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