A website sent advertisements by emails to users who interested in their product. Your task is to find a good model to predict if an advertisement will be clicked with given datasets. 

user_features.csv Download user_features.csv- features describing our users
product_feature.csv Download product_feature.csv- features describing products shown in the advertisements.
click_history.csv Download click_history.csv. - contains which products users had previously seen and whether that user ordered products in this website before.

** note this is not real data.

• Question 1: Data Understanding

Explore the basic information of the datasets. 

• Question 2: Data Cleaning and Preprocessing

Clean and preprocess the datasets (such as missing values, outliers, dummy, merging etc.). 

• Question 3: Model Generation and Evaluation

Please split the data into train and test sets with a ratio of 0.7:0.3. Build and optimize classification models you learned in this course. 

• Question 4: Which model has the best performance? What have you learned from the models you built?