a.Regression
1> Simple Linear Regression.
2> Multiple Linear Regression.
3> Polynomial Regression.
4> Support Vector Regression.
5> Decision Tree Regression.
6> Random Forest Regression.
7> Logistic Regression.
b. Classification
1> K-Nearest Neighbors.
2> Support Vector Machine.
3> Kernel SVM.
4> Navie Bayes.
5> Decision Tree Classification.
6> Random Tree Classification.
c. Clustering
1> K-Mean Clustering.
2> Hierarchial Clustering.
d.Association Rule Learning
1> Apriori.
2> Eclat.
e.Natural Language Processing
f. Deep Learning
1> Artifical Neural Network.
2> Convolution Neural Network.