Locality Sensitive Hashing and Collaborative Filtering on Yelp Data

Task 1: Jaccard based LSH

Implement LSH with Jaccard similarity using the yelp_train.csv dataset, focusing on identifying similar businesses with a Jaccard similarity of >= 0.5.

Task 2: Recommendation System

Build various types of recommendation systems to predict user ratings for businesses:

• Case 1: Item-based CF recommendation system with Pearson similarity.
• Case 2: Model-based recommendation system.
• Case 3: Hybrid recommendation system.