Applied Data Science - 5 : Modeling and Prediction | Kumaran Ponnambalam | Skillshare

Applied Data Science - 5 : Modeling and Prediction

Kumaran Ponnambalam, Dedicated to Data Science Education

Play Speed
  • 0.5x
  • 1x (Normal)
  • 1.25x
  • 1.5x
  • 2x
20 Lessons (4h 40m)
    • 1. About Applied Data Science Series

      8:12
    • 2. Types of Analytics

      12:08
    • 3. Types of Learning

      17:16
    • 4. Analyzing Results and Errors

      13:46
    • 5. Linear Regression

      19:00
    • 6. R Use Case : Linear Regression

      18:01
    • 7. Decision Trees

      10:42
    • 8. R Use Case : Decision Trees

      19:36
    • 9. Naive Bayes Classifier

      19:21
    • 10. R Use Case : Naive Bayes

      19:12
    • 11. Random Forests

      10:31
    • 12. R Use Case : Random Forests

      18:47
    • 13. K Means Clustering

      11:53
    • 14. R Use Case : K Means Clustering

      16:24
    • 15. Association Rules Mining

      11:30
    • 16. R Use Case : Association Rules Mining

      13:11
    • 17. ANN and SVM

      4:35
    • 18. Bagging and Boosting

      11:27
    • 19. Dimensionality Reduction

      7:28
    • 20. R Use Case : Advanced Methods

      17:18

About This Class

This class is part of the "Applied Data Science Series" on SkillShare presented by V2 Maestros. If you wish to go through the entire curriculum, please register for all the other courses and go through them in the sequence specified.

This course focuses on Modeling and Prediction. Different algorithms for supervised and unsupervised learning are explored. Use cases are presented for the major types of algorithms.