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DevelopmentData ScienceMachine Learning

Learn Machine Learning with Weka

Learn Machine Learning and Weka with this COurse
Rating: 3.3 out of 53.3 (16 ratings)
586 students
Created by Goh Ming Hui
Last updated 12/2018
English

What you'll learn

  • Machine Learning using Weka Software

Requirements

  • Computer Knowledge

Description

This is the bite size course to learn Weka and Machine Learning. You will learn Machine Learning which is the Model and Evaluation of CRISP Data Mining Process. You will learn Linear Regression, Kmeans Clustering, Agglomeration Clustering, KNN, Naive Bayes, Neural Network in this course. 

Content

  1. Getting Started

  2. Getting Started 2

  3. Data Mining Process

  4. Simple Linear Regression

  5. Regression in Weka

  6. KMeans Clustering

  7. KMeans Clustering in Weka

  8. Agglomeration Clustering

  9. Agglomeration Clustering in Weka

  10. Decision Tree: ID3 Algorithm

  11. Decision Tree in Weka

  12. KNN Classiifcation

  13. KNN in Weka

  14. Naive Bayes

  15. Naive Bayes in Weka

  16. What Algorithm to use?

  17. Model Evaluation

  18. Weka Advanced Attribute Selection

  19. Weka Advanced Data Visualizations

  20. Weka Model Selection and Deployment

Who this course is for:

  • Beginner Data Analyst and Data Scientist interested to learn Machine Learning and Weka.

Instructor

Goh Ming Hui
Offer affordable data science courses.
Goh Ming Hui
  • 3.1 Instructor Rating
  • 260 Reviews
  • 13,887 Students
  • 28 Courses

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, books and softwares assists people to step into new fields of Data Science, Internet of Things, Smart Cities and etc. before going into more advanced courses at Coursera and EdX, which are at University Level.

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