π¨βπ» Learn how to implement a model of machine learning to solve a real problem
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Study Case 1 - Predictive Analysis in Diamonds Store Predict price of diamonds based on size (x, y, z), depth, cut type, color etc 
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Study Case 2 - Sentiment Classification in Comment Classify sentiment of a sentences 
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Study Case 3 - House Price in Beijing Predictor (Predictive Analysis) Predict price of house in Beijing based on 26 features (building type, size, bathroom etc) 
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Study Case 4 - Recommendation System - Restaurant Recommender with Collaborative Filtering
- Restaurant Recommender with Content Base Filtering Filtering
 A project to create a recommendation system that recommend restaurants based on the history of restaurants that users have visited before and similarity of each restaurant's cuisine. The dataset contains Β±1000 rating data from users and Β±90 data of restaurants. 
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Study Case 5 - Film Recommender (Recommendation System) A project to create a recommendation system that recommends films based on the history of films that users have watched before and similarity of each film's genre. The dataset contains Β±20 milions rating data from users and Β±250k data of films.