Participated in Analytics Vidya Hackathon ( JOB-A-THON | May 2021 ). Public roc_auc_score - 0.8730946.
This Repository contains all code, reports and approach.
Happy Customer Bank is a mid-sized private bank that deals in all kinds of banking products, like Savings accounts, Current accounts, investment products, credit products, among other offerings. The bank also cross-sells products to its existing customers and to do so they use different kinds of communication like tele-calling, e-mails, recommendations on net banking, mobile banking, etc. In this case, the Happy Customer Bank wants to cross sell its credit cards to its existing customers. The bank has identified a set of customers that are eligible for taking these credit cards. Now, the bank is looking for your help in identifying customers that could show higher intent towards a recommended credit card, given:
- Customer details (gender, age, region etc.)
- Details of his/her relationship with the bank (Channel_Code,Vintage, 'Avg_Asset_Value etc.)
train.csv- ID,Gender,Age,Region_Code,Occupation,Channel_code,Vintage,Credit_Product,Avg_Account_balance,Is_Active,Is_Leadtest.csv- ID,Gender,Age,Region_Code,Occupation,Channel_code,Vintage,Credit_Product,Avg_Account_balance,Is_Activesample_submission- ID,Is_Lead
Code: Python Version: 3.8
For data wrangling and visualization: scikit-learn , Pandas Profiling ,SciPy
For predictive analytics: scikit-learn, LightGBM, Catboost
For Reporting: Google Slides
Build a classifier that predicts if the customer is a interested in credit card or not.