This books is not a "heavy" Artificial Intelligence tome. Instead it is a thought-provoking, instructive and very enjoyable read. It covers many of the everyday problems that web applications face: searching, clustering, relevance, etc.. In general, problems involving large quantities of typicall
Algorithms of the Intelligent Web
โ Scribed by Doug McIlwraith;
- Publisher
- Simon & Schuster
- Year
- 2023
- Tongue
- English
- Leaves
- 240
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.
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
โข Introduction to machine learning
โข Extracting structure from data
โข Deep learning and neural networks
โข How recommendation engines work
โฆ Table of Contents
Copyright
Brief Table of Contents
Table of Contents
Foreword
Preface
Acknowledgments
About this Book
Chapter 1. Building applications for the intelligent web
Chapter 2. Extracting structure from data: clustering and transforming your data
Chapter 3. Recommending relevant content
Chapter 4. Classification: placing things where they belong
Chapter 5. Case study: click prediction for online advertising
Chapter 6. Deep learning and neural networks
Chapter 7. Making the right choice
Chapter 8. The future of the intelligent web
Appendix. Capturing data on the web
Index
List of Figures
List of Tables
List of Listings
๐ SIMILAR VOLUMES
Web 2.0 applications provide a rich user experience, but the parts you can't see are just as important-and impressive. They use powerful techniques to process information intelligently and offer features based on patterns and relationships in data. Algorithms of the Intelligent Web shows readers how
Web 2.0 applications provide a rich user experience, but the parts you can't see are just as important-and impressive. They use powerful techniques to process information intelligently and offer features based on patterns and relationships in data. Algorithms of the Intelligent Web shows readers how