Buy Web and Network Data Science Book by Thomas Miller
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Home > Science, Technology & Agriculture > Technology: general issues > Engineering: general > Web and Network Data Science: Modeling Techniques in Predictive Analytics(FT Press Analytics)
Web and Network Data Science: Modeling Techniques in Predictive Analytics(FT Press Analytics)

Web and Network Data Science: Modeling Techniques in Predictive Analytics(FT Press Analytics)


     0     
5
4
3
2
1



Out of Stock


Notify me when this book is in stock
X
About the Book

Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics.   Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications.   Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.

Table of Contents:
Preface    v 1  Being Technically Inclined    1 2  Delivering a Message Online    13 3  Crawling and Scraping the Web    25 4  Testing Links, Look, and Feel    43 5  Watching Competitors    55 6  Visualizing Networks    69 7  Understanding Communities    95 8  Measuring Sentiment    119 9  Discovering Common Themes    171 10  Making Recommendations    201 11  Playing Network Games    223 12  What’s Next for the Web?    233 A  Data Science Methods    237 A.1  Databases and Data Preparation    240 A.2  Classical and Bayesian Statistics    242 A.3  Regression and Classification    245 A.4  Machine Learning    250 A.5  Data Visualization    252 A.6  Text Analytics    253 B  Primary Research Online    261 C  Case Studies    281 C.1  Email or Spam?    281 C.2  ToutBay Begins    284 C.3  Keyword Games: Dodgers and Angels    288 C.4  Enron Email Corpus and Network    291 C.5  Wikipedia Votes    292 C.6  Quake Talk    294 C.7  POTUS Speeches    295 C.8  Anonymous Microsoft Web Data    296 D  Code and Utilities    297 E  Glossary    313 Bibliography    321 Index    351  

About the Author :
THOMAS W. MILLER is faculty director of the Predictive Analytics program at Northwestern University. He has designed courses for the program, including Marketing Analytics, Advanced Modeling Techniques, Data Visualization, Web and Network Data Science, and the capstone course. He has taught extensively in the program and works with more than forty other faculty members in delivering training in predictive analytics and data science.   Miller is co-founder and director of product development at ToutBay, a publisher and distributor of data science applications. He has consulted widely in the areas of retail site selection, product positioning, segmentation, and pricing in competitive markets, and has worked with predictive models for over 30 years. Miller’s books include Modeling Techniques in Predictive Analytics (Revised and Expanded Edition), Modeling Techniques in Predictive Analytics with Python and R, Data and Text Mining: A Business Applications Approach, Research and Information Services: An Integrated Approach for Business, and a book about predictive modeling in sports, Without a Tout: How to Pick a Winning Team.   Before entering academia, Miller spent nearly 15 years in business IT in the computer and transportation industries. He also directed the A. C. Nielsen Center for Marketing Research and taught market research and business strategy at the University of Wisconsin—Madison.   He holds a Ph.D. in psychology (psychometrics) and a master’s degree in statistics from the University of Minnesota, and an MBA and master’s degree in economics from the University of Oregon.  


Best Sellers


Product Details
  • ISBN-13: 9780133887648
  • Publisher: Pearson Education (US)
  • Publisher Imprint: Pearson FT Press
  • Language: English
  • Series Title: FT Press Analytics
  • Weight: 1 gr
  • ISBN-10: 0133887642
  • Publisher Date: 19 Dec 2014
  • Binding: Digital download
  • No of Pages: 384
  • Sub Title: Modeling Techniques in Predictive Analytics


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Web and Network Data Science: Modeling Techniques in Predictive Analytics(FT Press Analytics)
Pearson Education (US) -
Web and Network Data Science: Modeling Techniques in Predictive Analytics(FT Press Analytics)
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Web and Network Data Science: Modeling Techniques in Predictive Analytics(FT Press Analytics)

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    Fresh on the Shelf


    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!