Machine Learning

Course Content

Total learning: 4 lessons

Part – 1

Part 1 Supervised Learning 

  1. Liner Regression 
  2. Logistics Regression 
  3. Support Vector Machines (SVM)
  4. Na¨ıve Bayes
  5. Ordinal Regression
  6. Multinomial Regression
  7. k-Nearest Neighbor Classification
  8. Decision Tree 
  9. GINI Dacesion Tree 
  10. Bootstrap Aggregating (Bagging),
  11. Random forest Resembling ,
  12. Support vector machine
  13. Neural Network
  14. Deep Learning  
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