Transforming raw data into a meaningful format is necessary for building effective models.
- Supervised Learning: Annotating datasets with correct labels (e.g., labeling images of apples vs. other fruits).
- Manual & Automated Labeling: Using human annotators or leveraging existing labeled datasets (e.g., Google reCAPTCHA).
- Feature Scaling & Encoding: Applying normalization and encoding to categorical variables.
- Encoding Categorical Variables: Converting categorical data into numerical format for machine learning models.