Find out how to use prebuilt Python libraries for predictive analytics and discover insights about the future.
Overview
Syllabus
Introduction
- Predict data in Python
- Road map
- Differentiate data types
- Python libraries and data import
- Handling missing values
- Convert categorical data into numbers
- Divide the data into test and train
- Feature scaling
- Introduction to predictive models
- Linear regression
- Polynomial regression
- Support Vector Regression (SVR)
- Decision tree regression
- Random forest regression
- Evaluation of predictive models
- Hyperparameter optimization
- Challenge: Hyperparameter optimization
- Solution: Hyperparameter optimization
- Next steps
Taught by
Isil Berkun
