This video explains the basics and mathematical intuition of Support Vector Machine (Classification and Regression)
The complete Series of Machine Learning is as below:
1. What is artificial intelligence
2. What is machine learning
3. Multiple regression using R part 1
4. Multiple regression using R part 2
5. What is R-Square and Adjusted R square
6. Variance and Bias
7. Multicollinearity
8. Heteroscedasticity
9. Confusion matrix
10. Principal component analysis and factor analysis Part 1
11. Principal component analysis and factor analysis Part 2
12. Cluster Analysis (Basics of Hierarchical Clustering) Part 1
13. Cluster Analysis (Similarity and Linkage method) Part 2
14. Cluster Analysis (Create Cluster using R) Part 3
15. Cluster Analysis (Identify K using R-NbClust) Part 4
16. Cluster Analysis (Basic of K-Mean) Part 5
17. Cluster Analysis (K-mean Using R) Part 6
18. Regularization Part 1 (Basics of Ridge Lasso Elastic Net)
19. Regularization Part 2 Using R (Ridge Lasso Elastic Net)
20. Logistic Regression Part 1 (Basics)
21. Logistic Regression Part 2 (Sigmoid Function)
22. Logistic Regression Part 3 (Assumptions and Point to remember)
23. Logistic Regression Part 4 Using R (Complete Explanation)
24. Logistic Regression Part 5 Nomogram
25. Support Vector Machine Part 1 (classification and regression)
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