This is the bite size course to learn Java Programming for Machine Learning and Statistical Learning with Weka library. In CRISP DM data mining process, machine learning is at the modeling and evaluation stage. 

You will need to know some Java programming, and you can learn Java programming from my "Create Your Calculator: Learn Java Programming Basics Fast" course.  You will learn Java Programming for machine learning and 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. Introduction

2. Getting Started

3. Getting Started 2

4. Getting Started 3

5. Data Mining Process

6. Data set

7. Split Training and Testing dataset

8. CReate Java Application using Netbeans with Weka Jar

9. Simple Linear Regression

10. LInear Regression using Weka and Java

11. LInear Regression using Weka and Java 2

12. LInear Regression using Weka and Java 3

13. KMeans Clustering

14. KMeans Clustering in Weka and Java

15. Agglomeration Clustering

16. Agglomeration Clustering in Weka and Java

17. Decision Tree ID3 ALgorithm

18. Decision Tree in Weka and Java

19. KNN Classification

20. KNN in Weka and Java

21. Naive Bayes Classification

22. Naive Bayes in Weka and Java

23. Neural Network Classification

24. Neural Network in Weka and Java

25. What Algorithm to Use?

26. Model Evaluation

27. Model Evaluation in Weka and Java

28. CReate a Data Mining Software

29. CReate a Data Mining Software 2