What you will learn

• Prepare data for analysis by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.

• Compare and contrast predictive models using simple linear, multiple linear, and polynomial regression methods.

• Examine data using descriptive statistics, data grouping, analysis of variance (ANOVA), and correlation statistics.

• Evaluate a model for overfitting and underfitting conditions and tune its performance using regularization and grid search.