Data Mining with RapidMiner

Learn the data mining process using RapidMiner.
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Data Mining with RapidMiner

Learn the data mining process using RapidMiner.
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About the Class

This is a bite-size course to learn data mining using RapidMiner. This course uses the CRISP-DM data mining process.

What will you learn in this course?

You will learn RapidMiner to do data understanding, data preparation, modeling, and 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.

Content

  1. Getting Started
  2. Getting Started 2
  3. Data Mining Process
  4. Download Data Set
  5. Read CSV
  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: Decision Tree ID3 Algorithm
  25. Modeling: Decision Tree ID3 Algorithm using RapdiMiner
  26. Modeling: Decision Tree ID3 Algorithm using RapidMiner
  27. Evaluation: Decision 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. Evaluation: Neural Network Classification using RapidMiner
  37. What Algorithm to Use?
  38. Model Evaluation
  39. K fold cross-validation using RapidMiner

Author

Svbook Pte Ltd

SVBook Pte. Ltd. started in April 2016. SVBook Pte. Ltd. offers affordable, easy to read Data Mining, Text Mining, Data Analytics, Programming books for professional and lifelong learning. SVBook Pte. Ltd. offers courses at EMHAcademy. SVBook Pte. Ltd. developed softwares over the time, and uploaded them at DSTK.Tech. SVBook Pte. Ltd. courses,...

School

Svbook Pte Ltd 's School

Requirements

You should have basic computer knowledge.

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What's Included

Language: English
Level: Beginner
Skills: RapidMiner, Data Mining, Programming, CRISP-DM
Age groups: 25-34 years
Duration: 1 hour 22 minutes
39 Videos
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