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

Applied Data Science - 5 : Modeling and Prediction

Kumaran Ponnambalam, Dedicated to Data Science Education

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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

Project Description

Using the caret package

Use the caret package to build models for all the datasets provided in the use cases. Use the same algorithm used in the example use case, but with the caret package. Compare the results between the caret package and the output seen in the use cases.

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