Preprocessing.ipynb contains useful information on Preprocessing when undertaking Machine Learning Tasks.
Dimensionality Reduction focusses on Dimesionality Reduction which is one of the steps undertaken when conducting Preprocessing.
The rest are images used in Preprocessing.ipynb for explanations and illustrations.
Preprocessing.ipynb touches on:
- Handling missing data
- Dealing with data types
- standardization, scaling, centering
- pipelining
- Feature engineering
- Dealing with Categorical Features
- Feature Selection
- Feature Extraction
Feature Engineering is a directory that delves deeper into Feature Engineering. It has two notebooks: Feature Engineering.ipynb and feature_engineering.ipynb