This chapter focuses on practical applications of Practical Project. You will learn essential concepts and techniques.
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Chapter Contents
- Project Overview - Analysis and grouping of customer data
- Data Preprocessing - Missing value handling, normalization, feature engineering
- Exploratory Data Analysis (EDA) - Understanding data distribution and correlation
- Clustering Implementation - Comparison of K-means and hierarchical clustering
- Visualization through Dimensionality Reduction - Visualizing clusters with PCA and t-SNE
- Segment Interpretation - Deriving business value
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