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Computer Science
Artificial Intelligence
Machine Learning
Feature Engineering for Machine Learning
1. Introduction to Feature Engineering
2. Foundational Concepts
3. Exploratory Data Analysis for Features
4. Data Cleaning and Preparation
5. Feature Scaling and Normalization
6. Categorical Feature Engineering
7. Feature Creation and Generation
8. Temporal Feature Engineering
9. Text Feature Engineering
10. Geospatial Feature Engineering
11. Feature Selection Methods
12. Dimensionality Reduction
13. Advanced Feature Engineering
14. Evaluation and Validation
15. Implementation and Best Practices
16. Common Pitfalls and Solutions
10.
Geospatial Feature Engineering
10.1.
Coordinate Features
10.1.1.
Latitude and Longitude
10.1.2.
Coordinate Transformations
10.1.3.
Coordinate System Conversions
10.2.
Distance Calculations
10.2.1.
Euclidean Distance
10.2.2.
Manhattan Distance
10.2.3.
Haversine Distance
10.2.4.
Great Circle Distance
10.3.
Spatial Relationships
10.3.1.
Point-in-Polygon
10.3.2.
Nearest Neighbor Distance
10.3.3.
Spatial Clustering
10.3.4.
Voronoi Diagrams
10.4.
Location-Based Features
10.4.1.
Administrative Boundaries
10.4.2.
Points of Interest Proximity
10.4.3.
Population Density
10.4.4.
Economic Indicators
10.5.
Geohashing and Spatial Indexing
10.5.1.
Geohash Encoding
10.5.2.
H3 Hexagonal Indexing
10.5.3.
Spatial Grid Features
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9. Text Feature Engineering
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11. Feature Selection Methods