By Douglas McIlwraith, Haralambos Marmanis, Dmitry Babenko

ISBN-10: 1617292583

ISBN-13: 9781617292583

Summary

Algorithms of the clever net, moment Edition teaches crucial techniques to algorithmic net information research, allowing you to create your personal computer studying purposes that crunch, munge, and wrangle information gathered from clients, internet purposes, sensors and web site logs.

Purchase of the print booklet encompasses a loose book in PDF, Kindle, and ePub codecs from Manning Publications.

About the Technology

Valuable insights are buried within the tracks internet clients depart as they navigate pages and functions. you could discover them by utilizing clever algorithms just like the ones that experience earned fb, Google, and Twitter a spot one of the giants of net facts trend extraction.

About the Book

Algorithms of the clever net, moment Edition teaches you ways to create desktop studying functions that crunch and wrangle facts accrued from clients, net purposes, and web site logs. during this absolutely revised version, you are going to examine clever algorithms that extract actual worth from information. Key computer studying options are defined with code examples in Python's scikit-learn. This publication publications you thru algorithms to seize, shop, and constitution information streams coming from the internet. you will discover advice engines and dive into class through statistical algorithms, neural networks, and deep learning.

What's Inside

  • Introduction to computer learning
  • Extracting constitution from data
  • Deep studying and neural networks
  • How advice engines work

About the Reader

Knowledge of Python is assumed.

About the Authors

Douglas McIlwraith is a computing device studying professional and knowledge technology practitioner within the box of web advertising. Dr. Haralambos Marmanis is a pioneer within the adoption of desktop studying strategies for commercial options. Dmitry Babenko designs functions for banking, assurance, and supply-chain administration. Foreword by means of Yike Guo.

Table of Contents

  1. Building purposes for the clever web
  2. Extracting constitution from info: clustering and reworking your facts
  3. Recommending suitable content
  4. Classification: putting issues the place they belong
  5. Case examine: click on prediction for on-line advertising
  6. Deep studying and neural networks
  7. Making definitely the right choice
  8. The way forward for the clever web
  9. Appendix - shooting information at the web

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Additional resources for Algorithms of the Intelligent Web

Sample text

For maximum generality and performance, both bias and noise should be minimized when collecting data. The curse of dimensionality y-axis Although the dataset contains only four features at the moment, you may wonder why we can’t collect hundreds or thousands of measurements from each of the flowers and let the algorithm do all the work. Despite the practical challenges in obtaining so many measurements, there are two fundamental problems when collecting data with high dimensionality that are particularly important when finding structure.

Despite the practical challenges in obtaining so many measurements, there are two fundamental problems when collecting data with high dimensionality that are particularly important when finding structure. The first problem is that the large number of dimensions increases the amount of space available for spreading data points. That is, if you keep the number of data points fixed and increase the number of attributes you want to use to describe them, the density of the points in your space decreases exponentially!

Let’s now return to each class of intelligent algorithm and discuss strategies for performance measurement. Although we’ll touch on how to evaluate intelligence, this section is largely about evaluating predictions (that is, for machine learning and predictive analytics). Evaluating (and defining) intelligence is a big subject and could fill a book like this on its own! 1 Evaluating intelligence In the preceding text, we mentioned Turing’s imitation game, but there may be a call to evaluate systems that are less grand in their approach to intelligence: for example, intelligent systems that play chess or compete on Jeopardy!

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Algorithms of the Intelligent Web by Douglas McIlwraith, Haralambos Marmanis, Dmitry Babenko


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