4 docs tagged with "Data Science"

Bloom Filters are probabilistic data structures used in applications where space efficiency is crucial, and approximate answers are acceptable, like database caching and network filtering.

Implement hierarchical clustering algorithms that build a hierarchy of clusters using either agglomerative or divisive methods. This feature will include visualizations to help users understand the clustering process.

Implement the K-Means clustering algorithm to partition data into K clusters based on feature similarity. This feature will include visualizations to help users understand the clustering process.

Implement Principal Component Analysis (PCA) to reduce the dimensionality of high-dimensional data while preserving its essential features. Visualize the transformed data to gain insights into underlying patterns.