- What is Machine Learning?
- Linear Regression Single Variable
- Linear Regression Multiple Variables
- Gradient Descent and Cost Function
- Save Model Using Joblib And Pickle
- Dummy Variables & One Hot Encoding
- Training and Testing Data
- Logistic Regression (Binary Classification)
- Logistic Regression (Multiclass Classification)
- Decision Tree
- Support Vector Machine (SVM)
- Random Forest
- K Fold Cross Validation
- K Means Clustering
- Naive Bayes Part 1
- Naive Bayes Part 2
- Hyper parameter Tuning (GridSearchCV)
Support Vector Machine (SVM)
Exercise: Open above notebook from github and go to the end.
Support vector machine is a popular classification algorithm. This tutorial covers some theory first and then goes over python coding to solve iris flower classification problem using svm and sklearn library. We also cover different parameters such as gamma, regularization and how to fine tune svm classifier using these parameters.