- 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)
Linear Regression Single Variable
Correction: at 6:53, use reg.predict([]) instead of reg.predict(3300) as api specification has changed.
In this tutorial we will predict home prices using linear regression. We use training data that has home areas in square feet and corresponding prices and train a linear regression model using sklearn linearregression class. Later on predict method is used on linearregression object to make actual forecast.