Douglas McIlwraith, Haralambos Marmanis, Dmitry Babenko's Algorithms of the Intelligent Web PDF

By Douglas McIlwraith, Haralambos Marmanis, Dmitry Babenko

ISBN-10: 1617292583

ISBN-13: 9781617292583


Algorithms of the clever internet, moment Edition teaches an important methods to algorithmic internet information research, allowing you to create your personal laptop studying purposes that crunch, munge, and wrangle information accumulated from clients, net functions, sensors and web site logs.

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

About the Technology

Valuable insights are buried within the tracks net clients depart as they navigate pages and purposes. 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 internet info trend extraction.

About the Book

Algorithms of the clever net, moment Edition teaches you ways to create laptop studying functions that crunch and wrangle info accrued from clients, internet functions, and web site logs. during this absolutely revised variation, you are going to examine clever algorithms that extract genuine price from info. Key desktop studying options are defined with code examples in Python's scikit-learn. This publication courses you thru algorithms to seize, shop, and constitution information streams coming from the internet. you are going to discover suggestion engines and dive into category through statistical algorithms, neural networks, and deep learning.

What's Inside

  • Introduction to computing device learning
  • Extracting constitution from data
  • Deep studying and neural networks
  • How suggestion engines work

About the Reader

Knowledge of Python is assumed.

About the Authors

Douglas McIlwraith is a computer studying professional and information technology practitioner within the box of web advertising. Dr. Haralambos Marmanis is a pioneer within the adoption of computing device studying suggestions for commercial recommendations. Dmitry Babenko designs purposes for banking, coverage, and supply-chain administration. Foreword by means of Yike Guo.

Table of Contents

  1. Building functions for the clever web
  2. Extracting constitution from info: clustering and remodeling your info
  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 the appropriate choice
  8. The way forward for the clever web
  9. Appendix - taking pictures facts at the web

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Extra info for Algorithms of the Intelligent Web

Example text

When you provide a score, you may not always be able to follow up on the behavior of that user in the future. Also, in these cases you’re usually not attempting to provide the answer but rather some indicator that’s correlated with a target variable (such as creditworthiness). Although the ROC curve can be used in these cases, there can be a few more hoops to jump through to get there. 7 Important notes about intelligent algorithms Thus far we’ve covered a lot of introductory material. By now, you should have a fairly good, albeit high-level, understanding of intelligent algorithms and how you’re going to use them.

You shouldn’t assume that all algorithms on all datasets will run within the response-time limits of your application. You should test the performance of your algorithm within the range of your operating characteristics. 3 Size matters! When we talk about intelligent applications, size does matter! The size of your data comes into the picture in two ways. The first is related to the responsiveness of the application, as mentioned earlier. The second is related to your ability to obtain meaningful results on a large dataset.

20 Building simple classifiers in a low number of dimensions is easy, but increasing the number of dimensions makes it hard to understand what’s happening. ” This is especially important when it comes to building solutions using ML approaches. Understanding the problem domain is key here, and deriving a set of features that exposes the underlying phenomena under investigation can mean all the difference to classification accuracy and generalization. It’s not good enough to throw all of your data at a classifier and hope for the best!

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

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