Feature Engineering
Learning Outcomes
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What’s Included
Course Introduction
Course Introduction
In this lesson, we get a preview of the course ahead.
The Value of Feature Scaling
The Value of Feature Scaling
In this lesson, we'll learn why it can be useful to scale your data before applying a machine learning algorithm.
Feature Scaling with Min and Max Values
Feature Scaling with Min and Max Values
In this lesson, we'll learn how to scale our features in Python using the absolute maximum and min/max scaling techniques.
Standardization and Robust Scaling
Standardization and Robust Scaling
In this lesson, we'll learn how to scale our features in Python using standardization and robust scaling.
Value of Feature Selection
Value of Feature Selection
In this lesson, we'll learn how to determine which features have the most predictive power.
Applying Feature Selection
Applying Feature Selection
In this lesson, we'll learn how to use feature selection functions to find which predictor features are the most useful for our model.
Dimensionality Reduction
Dimensionality Reduction
In this lesson, we'll learn about dimensionality reduction, and how it can remove the majority of values from our dataset while minimizing the loss to predictive power.
Principal Component Analysis
Principal Component Analysis
In this lesson, we'll learn how to apply principle component analysis in Python.
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