Data For Good Hackathon

1. Hackathon_AI_ML.ipynb comprises of the preliminary data analysis including data cleaning and imputation.
2. predictions.ipynb comprises of the ML techniques - Random Forest and Logistic Regression - and their results.
3. random_forest_pri.ipynb also consist of the Random Forest approach along with the importance of features.

The code ("Code") in this repository was created solely by the student teams during a coding competition hosted by JPMorgan Chase Bank, N.A. ("JPMC"). JPMC did not create or contribute to the development of the Code. This Code is provided AS IS and JPMC makes no warranty of any kind, express or implied, as to the Code, including but not limited to, merchantability, satisfactory quality, non-infringement, title or fitness for a particular purpose or use.