Mastering Data Mining
eBook - ePub

Mastering Data Mining

Advanced Data Mining

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Mastering Data Mining

Advanced Data Mining

About this book

Understand how patterns can be identified in data

Mastering Data Mining: Advanced Data Mining brings your study of data mining into focus. This Cybellium study guide connects data preparation, pattern discovery and evaluation and interpretation, helping you see how the ideas fit together.

Develop a more connected understanding of the subject and the questions it raises. Use it to revisit the subject, connect its moving parts and identify the areas you want to study more deeply.

Build your understanding

  • Understand the role of data preparation.
  • Explore the relationships behind pattern discovery.
  • Examine the choices and questions involving evaluation and interpretation.
  • Bring individual concepts together into a more coherent understanding of the subject.

Who this guide is for

For readers building on an existing foundation with an interest in data mining. Use the book for focused study, revision or the next stage of your professional learning, returning to the ideas most relevant to your goals.

Your included Cybellium learning bonus

  • One complimentary month of Cybellium access.
  • One additional Cybellium guide download of your choice.
  • Access to the Cybellium Cybersecurity Knowledge Hub and premium learning resources during the included access period.

Activate your unique voucher at www.cybellium.com/signup to begin your included month and select your additional guide.

The included voucher is valid for one-time use only and cannot be combined with another offer.

Continue your learning with Mastering Data Mining.

Information

Publisher
YouGuide
Year
2024
eBook ISBN
9798862657357

Table of contents

  1. Mastering Data Mining
  2. 1. Introduction to Advanced Data Mining
  3. 2. Data Mining Foundations
  4. 3. Data Preparation and Preprocessing
  5. 4. Exploratory Data Analysis (EDA)
  6. 5. Supervised Learning Techniques
  7. 6. Unsupervised Learning Techniques
  8. 7. Advanced Classification Methods
  9. 8. Advanced Clustering and Segmentation
  10. 9. Text and Web Mining
  11. 10. Time Series and Sequence Mining
  12. 11. Big Data Mining
  13. 12. Data Mining Tools and Platforms
  14. 13. Model Evaluation and Validation
  15. 14. Data Mining in Business and Industry
  16. 15. Data Mining Challenges and Pitfalls
  17. 16. Ethics, Privacy, and Legal Issues
  18. 17. Emerging Trends and Innovations
  19. 18. The Future of Data Mining
  20. 19. Hands-On Projects and Case Studies
  21. 20. Resources and Further Learning

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