CS328-2022 Notes

Course Description

Logistics

Contributing to CS328 Notes
Deadlines

Foundations

Data Representations
[CODE] 🧑‍💻Data Representations
Distance Function
Object Representations
Central Limit Theorem
Markov and Chebyshev Inequalities
Chernoff Bound
Plot of chernoff bound

Clustering and low-rank approximations

Clustering
K-means
Lloyd’s algorithm, convergence?
Why does k-means++ work?
Hierarchical Clustering
Densest Subgraphs
Densest Subgraph
Expansion and Conductance of a Graph
Graph Laplacian and its Eigenvalues
Relation between second eigenvalue of Laplacian and Spectral Clustering
Mixture Models
Gaussian Annulus Theorem
Singular Valued Decomposition (SVD)
Applications of SVD
SVD in Gaussian Mixture Model
Frobenius Norm and Low Rank Approaximation
Low rank approximation in Mixture Models and Recommendation systems

Dealing with massive data

Streaming Models and Answering Inclusion Queries
Bloom Filters
Linear Counting
Flajolet-Martin Sketch

Selected topics from NPTEL-Scalable Data Science Course

Finding Near Neighbors
Locality Sensitive Hashing
Building LSH Table
Randomized Numerical Linear Algebra: Random Projection

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By Students of CS328 2022
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