Algorithms of the Intelligent Web

Author: Douglas G McIlwraith
Publisher: Manning Publications
ISBN: 1617292583
Release Date: 2016-09-08
Genre: Computers

Summary 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. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. 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 Introduction to machine learning Extracting structure from data Deep learning and neural networks How recommendation engines work About the Reader Knowledge of Python is assumed. About the Authors Douglas McIlwraith is a machine learning expert and data science practitioner in the field of online advertising. Dr. Haralambos Marmanis is a pioneer in the adoption of machine learning techniques for industrial solutions. Dmitry Babenko designs applications for banking, insurance, and supply-chain management. Foreword by Yike Guo. Table of Contents 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 Appendix - Capturing data on the web

ALGORITHMS OF THE INTELLIGENT WEB

Author: Haralambos Marmanis
Publisher:
ISBN: 9350040336
Release Date: 2011-03-01
Genre:

Special Features: Learning Elements:· How to create recommendations just like those on Netflix and Amazon· How to implement Google's Pagerank algorithm· How to discover matches on social-networking sites· How to organize the discussions on your favorite news group· How to select topics of interest from shared bookmarks· How to leverage user clicks· How to categorize emails based on their content· How to build applications that do targeted advertising· How to implement fraud detection About The Book: Algorithms of the Intelligent Web is an example-driven blueprint for creating applications that collect, analyze, and act on the massive quantities of data users leave in their wake as they use the web. You'll learn how to build Amazon- and Netflix-style recommendation engines, and how the same techniques apply to people matches on social-networking sites. See how click-trace analysis can result in smarter ad rotations. With a plethora of examples and extensive detail, this book shows you how to build Web 2.0 applications that are as smart as your users.

Algorithms of the Intelligent Web

Author: Haralambos Marmanis
Publisher: Manning Publications
ISBN: UOM:39076002811862
Release Date: 2009
Genre: Computers

Provides information on creating applications that collect, analyze, and act on the data that is left by users on the Web.

The Intelligent Web

Author: Gautam Shroff
Publisher: OUP Oxford
ISBN: 9780191664625
Release Date: 2013-11-28
Genre: Computers

As we use the Web for social networking, shopping, and news, we leave a personal trail. These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of "Web intelligence", as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected. Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.

Data Analytics

Author: Thomas A. Runkler
Publisher: Springer
ISBN: 9783658140755
Release Date: 2016-07-26
Genre: Computers

This book is a comprehensive introduction to the methods and algorithms of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. This book has been used for more than ten years in the Data Mining course at the Technical University of Munich. Much of the content is based on the results of industrial research and development projects at Siemens.

Autonomous Intelligent Vehicles

Author: Hong Cheng
Publisher: Springer Science & Business Media
ISBN: 1447122801
Release Date: 2011-11-15
Genre: Computers

This important text/reference presents state-of-the-art research on intelligent vehicles, covering not only topics of object/obstacle detection and recognition, but also aspects of vehicle motion control. With an emphasis on both high-level concepts, and practical detail, the text links theory, algorithms, and issues of hardware and software implementation in intelligent vehicle research. Topics and features: presents a thorough introduction to the development and latest progress in intelligent vehicle research, and proposes a basic framework; provides detection and tracking algorithms for structured and unstructured roads, as well as on-road vehicle detection and tracking algorithms using boosted Gabor features; discusses an approach for multiple sensor-based multiple-object tracking, in addition to an integrated DGPS/IMU positioning approach; examines a vehicle navigation approach using global views; introduces algorithms for lateral and longitudinal vehicle motion control.

Collective Intelligence in Action

Author: Satnam Alag
Publisher: Manning Publications
ISBN: 1933988312
Release Date: 2008
Genre: Computers

Provides information on using a Java-based CI toolkit to mine information to build more effective Web sites.

Programming Collective Intelligence

Author: Toby Segaran
Publisher: "O'Reilly Media, Inc."
ISBN: 9780596550684
Release Date: 2007-08-16
Genre: Computers

Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect

The Master Algorithm

Author: Pedro Domingos
Publisher: Basic Books
ISBN: 9780465061921
Release Date: 2015-09-22
Genre: Computers

"Wonderfully erudite, humorous, and easy to read." --KDNuggets In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner-the Master Algorithm-and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.

Algorithms

Author: Robert Sedgewick
Publisher: Addison-Wesley Professional
ISBN: 9780133847260
Release Date: 2014-02-01
Genre: Computers

This book is Part II of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms , the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part II contains Chapters 4 through 6 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts. The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants. Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.

Understanding Machine Learning

Author: Shai Shalev-Shwartz
Publisher: Cambridge University Press
ISBN: 9781107057135
Release Date: 2014-05-19
Genre: Computers

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

The Formula

Author: Luke Dormehl
Publisher: Penguin
ISBN: 9780698158849
Release Date: 2014-11-04
Genre: Computers

A fascinating guided tour of the complex, fast-moving, and influential world of algorithms—what they are, why they’re such powerful predictors of human behavior, and where they’re headed next. Algorithms exert an extraordinary level of influence on our everyday lives - from dating websites and financial trading floors, through to online retailing and internet searches - Google's search algorithm is now a more closely guarded commercial secret than the recipe for Coca-Cola. Algorithms follow a series of instructions to solve a problem and will include a strategy to produce the best outcome possible from the options and permutations available. Used by scientists for many years and applied in a very specialized way they are now increasingly employed to process the vast amounts of data being generated, in investment banks, in the movie industry where they are used to predict success or failure at the box office and by social scientists and policy makers. What if everything in life could be reduced to a simple formula? What if numbers were able to tell us which partners we were best matched with – not just in terms of attractiveness, but for a long-term committed marriage? Or if they could say which films would be the biggest hits at the box office, and what changes could be made to those films to make them even more successful? Or even who is likely to commit certain crimes, and when? This may sound like the world of science fiction, but in fact it is just the tip of the iceberg in a world that is increasingly ruled by complex algorithms and neural networks. In The Formula, Luke Dormehl takes readers inside the world of numbers, asking how we came to believe in the all-conquering power of algorithms; introducing the mathematicians, artificial intelligence experts and Silicon Valley entrepreneurs who are shaping this brave new world, and ultimately asking how we survive in an era where numbers can sometimes seem to create as many problems as they solve.

What Algorithms Want

Author: Ed Finn
Publisher: MIT Press
ISBN: 9780262035927
Release Date: 2017-03-10
Genre: Computers

The gap between theoretical ideas and messy reality, as seen in Neal Stephenson, Adam Smith, and Star Trek.

Artificial Intelligence

Author: Stuart Russell
Publisher: Createspace Independent Publishing Platform
ISBN: 1537600311
Release Date: 2016-09-10
Genre:

Artificial Intelligence: A Modern Approach offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.

Data Structures and Algorithms with JavaScript

Author: Michael McMillan
Publisher: "O'Reilly Media, Inc."
ISBN: 9781449373955
Release Date: 2014-03-10
Genre: Computers

As an experienced JavaScript developer moving to server-side programming, you need to implement classic data structures and algorithms associated with conventional object-oriented languages like C# and Java. This practical guide shows you how to work hands-on with a variety of storage mechanisms—including linked lists, stacks, queues, and graphs—within the constraints of the JavaScript environment. Determine which data structures and algorithms are most appropriate for the problems you’re trying to solve, and understand the tradeoffs when using them in a JavaScript program. An overview of the JavaScript features used throughout the book is also included. This book covers: Arrays and lists: the most common data structures Stacks and queues: more complex list-like data structures Linked lists: how they overcome the shortcomings of arrays Dictionaries: storing data as key-value pairs Hashing: good for quick insertion and retrieval Sets: useful for storing unique elements that appear only once Binary Trees: storing data in a hierarchical manner Graphs and graph algorithms: ideal for modeling networks Algorithms: including those that help you sort or search data Advanced algorithms: dynamic programming and greedy algorithms