CampusAI
DS
ML
RL
Research
Data Science
Dimensionality reduction
Dimensionality reduction: Algebraic Background
The curse of dimensionality, SVD
Dimensionality reduction: Algorithms
PCA, KPCA, MDS, Isomap, AutoEncoders
Mining Massive Datasets
Finding Similar Items: When $O(n^2)$ is not fast enough
Shingling, Minhashing, LSH
Frequent Itemsets
Market-Basket Model, Association Rules, A-Priori Algorithm
Mining Streams
Sampling, Bloom Filtering, Sliding Windows DGIM, Count Distinct Problem, Flajolet-Martin, HyperLogLog
Recommender Systems
Collaborative filtering, Content-based
Graphs
Graphs: Ranking the WWW
PageRank, Topic-Specific PageRank, TrustRank, SimRank, Hubs-and-Authorities
Graphs: Clustering
Connectivity Measures, Spectral Clustering, Overlapping Community Detection