Unit 1

• ·        Kmeans with numericals
• ·        kmeans++ with numericals
• ·        Kmedian with numericals
• ·        kmedoid with numericals
• ·        Kmeans intuitio

Unit 2

• ·        Anomaly detection and Types
• ·        Gaussian distribution and steps
• ·        Isolation forest and its concept
• ·        Hierarchical clustering and types
• ·        DBSCAN imp

Unit 3 

• ·        Explain the clustering metrics read all or any 4-5 metrics ?

Unit 4

• ·        Reinforcement learning and terms used in that
• ·        Approaches to implement reinforcement learn
• ·        In policy deterministic and stochastic
• ·        Bellman Equation

Unit 5

• ·        Q learning and terms or components used
• ·        Q learning algorithms process
• ·        Deep q network architecture

Unit 6

• ·        Recommender system how it works 
• ·        Types of recommender system
• ·        All similarity measures like Euclidian, cosine etc
• ·        All types of recommender system
• ·        TIIDF