Development [udemy.com] Machine Learning with Java and Weka

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27 Авг 2018
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DESCRIPTION:

What you'll learn

  • Create a data product using Weka and Java
Requirements
  • Computer Skills, Java Programming
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
Who this course is for:
  • Beginner Data Analyst or Data Scientist interested in using Weka in Java
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