Reddit Reddit reviews Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

We found 3 Reddit comments about Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems). Here are the top ones, ranked by their Reddit score.

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Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
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3 Reddit comments about Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems):

u/alk509 · 2 pointsr/programming

I really liked the Witten & Frank book (we used it in my intro to machine learning class a few years ago.) It's probably showing its age now, though - they're due for a new edition...

I'm pretty sure The Elements of Statistical Learning is available as a PDF somewhere (check /r/csbooks.) You may find it a little too high-level, but it's a classic and just got revised last year, I think.

Also, playing around with WEKA is always fun and illuminating.

u/CSMastermind · 2 pointsr/AskComputerScience

Senior Level Software Engineer Reading List


Read This First


  1. Mastery: The Keys to Success and Long-Term Fulfillment

    Fundamentals


  2. Patterns of Enterprise Application Architecture
  3. Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions
  4. Enterprise Patterns and MDA: Building Better Software with Archetype Patterns and UML
  5. Systemantics: How Systems Work and Especially How They Fail
  6. Rework
  7. Writing Secure Code
  8. Framework Design Guidelines: Conventions, Idioms, and Patterns for Reusable .NET Libraries

    Development Theory


  9. Growing Object-Oriented Software, Guided by Tests
  10. Object-Oriented Analysis and Design with Applications
  11. Introduction to Functional Programming
  12. Design Concepts in Programming Languages
  13. Code Reading: The Open Source Perspective
  14. Modern Operating Systems
  15. Extreme Programming Explained: Embrace Change
  16. The Elements of Computing Systems: Building a Modern Computer from First Principles
  17. Code: The Hidden Language of Computer Hardware and Software

    Philosophy of Programming


  18. Making Software: What Really Works, and Why We Believe It
  19. Beautiful Code: Leading Programmers Explain How They Think
  20. The Elements of Programming Style
  21. A Discipline of Programming
  22. The Practice of Programming
  23. Computer Systems: A Programmer's Perspective
  24. Object Thinking
  25. How to Solve It by Computer
  26. 97 Things Every Programmer Should Know: Collective Wisdom from the Experts

    Mentality


  27. Hackers and Painters: Big Ideas from the Computer Age
  28. The Intentional Stance
  29. Things That Make Us Smart: Defending Human Attributes In The Age Of The Machine
  30. The Back of the Napkin: Solving Problems and Selling Ideas with Pictures
  31. The Timeless Way of Building
  32. The Soul Of A New Machine
  33. WIZARDRY COMPILED
  34. YOUTH
  35. Understanding Comics: The Invisible Art

    Software Engineering Skill Sets


  36. Software Tools
  37. UML Distilled: A Brief Guide to the Standard Object Modeling Language
  38. Applying UML and Patterns: An Introduction to Object-Oriented Analysis and Design and Iterative Development
  39. Practical Parallel Programming
  40. Past, Present, Parallel: A Survey of Available Parallel Computer Systems
  41. Mastering Regular Expressions
  42. Compilers: Principles, Techniques, and Tools
  43. Computer Graphics: Principles and Practice in C
  44. Michael Abrash's Graphics Programming Black Book
  45. The Art of Deception: Controlling the Human Element of Security
  46. SOA in Practice: The Art of Distributed System Design
  47. Data Mining: Practical Machine Learning Tools and Techniques
  48. Data Crunching: Solve Everyday Problems Using Java, Python, and more.

    Design


  49. The Psychology Of Everyday Things
  50. About Face 3: The Essentials of Interaction Design
  51. Design for Hackers: Reverse Engineering Beauty
  52. The Non-Designer's Design Book

    History


  53. Micro-ISV: From Vision to Reality
  54. Death March
  55. Showstopper! the Breakneck Race to Create Windows NT and the Next Generation at Microsoft
  56. The PayPal Wars: Battles with eBay, the Media, the Mafia, and the Rest of Planet Earth
  57. The Business of Software: What Every Manager, Programmer, and Entrepreneur Must Know to Thrive and Survive in Good Times and Bad
  58. In the Beginning...was the Command Line

    Specialist Skills


  59. The Art of UNIX Programming
  60. Advanced Programming in the UNIX Environment
  61. Programming Windows
  62. Cocoa Programming for Mac OS X
  63. Starting Forth: An Introduction to the Forth Language and Operating System for Beginners and Professionals
  64. lex & yacc
  65. The TCP/IP Guide: A Comprehensive, Illustrated Internet Protocols Reference
  66. C Programming Language
  67. No Bugs!: Delivering Error Free Code in C and C++
  68. Modern C++ Design: Generic Programming and Design Patterns Applied
  69. Agile Principles, Patterns, and Practices in C#
  70. Pragmatic Unit Testing in C# with NUnit

    DevOps Reading List


  71. Time Management for System Administrators: Stop Working Late and Start Working Smart
  72. The Practice of Cloud System Administration: DevOps and SRE Practices for Web Services
  73. The Practice of System and Network Administration: DevOps and other Best Practices for Enterprise IT
  74. Effective DevOps: Building a Culture of Collaboration, Affinity, and Tooling at Scale
  75. DevOps: A Software Architect's Perspective
  76. The DevOps Handbook: How to Create World-Class Agility, Reliability, and Security in Technology Organizations
  77. Site Reliability Engineering: How Google Runs Production Systems
  78. Cloud Native Java: Designing Resilient Systems with Spring Boot, Spring Cloud, and Cloud Foundry
  79. Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation
  80. Migrating Large-Scale Services to the Cloud
u/great-pumpkin · 1 pointr/cogsci

'Artificial Intelligence: A Modern Approach' (it has machine learning and maybe less, datamining) is all I've used (besides Mitchell's one, that I'm anti-recommending), so I can't positively recommend any new ones. But there are several new titles. I'd try reading around the web to get an overview (or borrow one, even Mitchell's, from a library). Then, when you believe you know better what you're looking for look at books. I mean I could randomly pick one of the newer ones on Amazon but that's what it'd be. Chris Bishop (mentioned in the other reply) is a good writer + smart guy, I've been meaning to get that book of his; he's probably a safe bet but, reading around on the web first can't hurt either. The Weka-using datamining book might be an easy place to start, it's got a complete Java toolkit (which you can download free independently), Chris Bishop's book looks advanced. I might say Wikipedia but it doesn't look that helpful.