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Feature Engineering

Data preprocessing, feature extraction, and selection techniques.

Course Duration: 5 hours​

What You'll Learn​

  • Data cleaning and preprocessing
  • Feature creation and transformation
  • Feature selection methods
  • Handling missing data
  • Encoding categorical variables
  • Feature scaling and normalization

Prerequisites​

  • Python and Pandas
  • Basic ML knowledge

Course Modules​

  1. Introduction to Feature Engineering
  2. Handling Missing Values
  3. Outlier Detection and Treatment
  4. Categorical Encoding
  5. Feature Scaling
  6. Feature Creation
  7. Polynomial Features
  8. Feature Selection Methods
  9. Automated Feature Engineering
  10. Project: Feature Pipeline

Techniques Covered​

  • One-Hot / Label Encoding
  • StandardScaler / MinMaxScaler
  • SelectKBest / RFE
  • Featuretools (automated)