- 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)
Logistic Regression (Binary Classification)
Exercise: Open above notebook from github and go to the end.
Logistic regression is used for classification problems in machine learning. This tutorial will show you how to use sklearn logisticregression class to solve binary classification problem to predict if a customer would buy a life insurance. At the end we have an interesting exercise for you to solve.