Rabu, 27 Maret 2013

Wow! eBook: Data Mining, 3rd Edition - 2 new eBooks


Wow! eBook: Data Mining, 3rd Edition - 2 new eBooks

Link to Wow! eBook

Data Mining, 3rd Edition

Posted: 27 Mar 2013 05:33 AM PDT

Data Mining, 3rd Edition

Book Description

Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.

Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research.

  • Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects
  • Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
  • Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks-in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization

Table of Contents
Part I: Introduction to Data Mining
Chapter 1. What’s It All About?
Chapter 2. Input: Concepts, Instances, Attributes
Chapter 3. Output: Knowledge Representation
Chapter 4. Algorithms: The Basic Methods
Chapter 5. Credibility: Evaluating What’s Been Learned

Part II: Advanced Data Mining
Chapter 6. Implementations: Real Machine Learning Schemes
Chapter 7. Data Transformation
Chapter 8. Ensemble Learning
Chapter 9. Moving On: Applications and Beyond

Part III: The Weka Data MiningWorkbench
Chapter 10. Introduction to Weka
Chapter 11. The Explorer
Chapter 12. The Knowledge Flow Interface
Chapter 13. The Experimenter
Chapter 14. The Command-Line Interface
Chapter 15. Embedded Machine Learning
Chapter 16. Writing New Learning Schemes
Chapter 17. Tutorial Exercises for the Weka Explorer

Book Details

  • Paperback: 664 pages
  • Publisher: Morgan Kaufmann; 3rd Edition (January 2011)
  • Language: English
  • ISBN-10: 0123748569
  • ISBN-13: 978-0123748560
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Akka Concurrency

Posted: 27 Mar 2013 05:20 AM PDT

Akka Concurrency

Book Description

Writing truly concurrent software on the Java Virtual Machine just got a whole lot easier. The Akka Toolkit takes the sting out of coding for multiple cores, multiple processors, and even multiple machines.

Akka Concurrency will show you what it means to design and write software in the paradigm of Akka. You’ll learn how to think about your software in new and exciting ways that will allow you to express your designs naturally, allowing you to focus on the business of your software more than on the concurrency of it. This book picks up where the Akka documentation leaves off, exploring the how and the why of Akka, in a way that will empower you to grow your applications to new levels of scalability, responsiveness, and performance.

Table of Contents
Chapter 1. Preface
Chapter 2. Concurrency and Parallelism
Chapter 3. Set Up Akka
Chapter 4. Akka Does Concurrency
Chapter 5. Actors
Chapter 6. Akka Testing
Chapter 7. Systems, Contexts, Paths, and Locations
Chapter 8. Supervision and DeathWatch
Chapter 9. Being Stateful
Chapter 10. Routing Messages
Chapter 11. Dispatchers and Mailboxes
Chapter 12. Coding in the Future
Chapter 13. Networking with I/O
Chapter 14. Going Multi-Node with Remote Actors
Chapter 15. Sharing Data with Agents
Chapter 16. Granular Concurrency with Dataflow
Chapter 17. Patterns for Akka Programming
Chapter 18. Antipatterns for Akka Programming
Chapter 19. Growing Your App with Add-On Modules
Chapter 20. Using Akka from Java
Chapter 21. Now that You’re an Akka Coder

Book Details

  • Paperback: 515 pages
  • Publisher: Artima Inc (February 2013)
  • Language: English
  • ISBN-10: 0981531660
  • ISBN-13: 978-0981531663
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