### Data Mining with RapidMiner

This is the bite size course to learn Data Mining using RapidmIner. This course uses CRISP DM data mining process.

You will learn RapidMiner to do data understanding, data preparation, modeling, Evaluation. You will be able to train your own prediction models with naive bayes, decision tree, knn, neural network, linear regression, and evaluate your models very soon after learning the course.

You can take the course as follow and you can take an exam at EMHAcademy to get SVBook Advance Certificate in Data Science using DSTK, Excel, RapidMiner:

- Introduction to Data and Text Mining using DSTK 3

- Data Mining with RapidMiner

- Learn Microsoft Excel Basics Fast

- Learn Data Aalysis using Microsoft Excel Basics Fast.

Content

1. Getting Started

2. Getting Started 2

3. Data Mining Process

6. Data Understanding: Statistics

7. Data Understanding: Scatterplot

8. Data Understanding: Line

9. Data Understanding: Bar

10. Data Understanding: Histogram

11. Data Understanding: BoxPLot

12. Data Understanding: Pie

13. Data Understanding: Scatterplot Matrix

14. Data Preparation: Normalization

15. Data Preparation: Replace Missing Values

16. Data Preparation: Remove Duplicates

17. Data Preparation: Detect Outlier

18. Modeling: Simple Linear Regression

19. MOdeling: SImple Linear Regression using RapidMiner

20. MOdeling: KMeans CLustering

21. Modeling: KMeans Clustering using RapidmIner

22. Modeling: Agglomeration CLustering

23. Modeling: Agglomeration Clustering using RapidmIner

24. Modeling: Decison Tree ID3 Algorithm

25. Modeling: Decision Tree ID3 Algorithm using RapdimIner

26. Modeling: Decison Tree ID3 Algorithm using RapidMiner

27. Evaluation: Decsion Tree ID3 Algorithm using RapidmIner

28. MOdeling: KNN Classification

29. Modeling: KNN CLassification using RapidmIner

30. Evaluation: KNN Classification using RapidmIner

31. Modeling Naive BAyes CLassification

32. MOdeling: Naive Bayes Classification using RapidmIner

33. Evaluation: Naive Bayes Classification using RapidMIner

34. MOdeling: Neural Network Classification

35. Modeling: Neural Network Classification using RapidmIner

36. Evauation: Neural Network Classification using RapidmIner

37. What Algorithm to USe?

38. MOdel Evaluation

39. k fold cross validation using RapdimIner

13.99

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