Hello! This was a project in Python that was created for the Python for Data Science course at New York University. The question we wanted to answer: can we predict whether bank clients will subscribe to fixed-term deposit products (for example, CDs) based on a number of categorical and numerical features? All work was obviously done in Python. Other team members were Chaitra Hedge and Aakash Kaku.
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Analyzed the prior marketing campaigns of a Portuguese Bank using various ML techniques like Logistic Regression, Random Forests,Decision Trees, Gradient Boosting and AdaBoost and predicted if the user will buy the Bank’s term deposit or not
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Recommended, the marketing team, ways to better target customers using feature importance maps and business intuition
Instructions to run the code:
- Make sure the data file ("bank-additional-full.csv") is in the same directory as the ipython notebook or edit the ipython notebook accordingly.
- Make sure to run the notebook in python 3 environment. Make sure all the dependencies used in the notebook are installed in the local machine.
- Run the code sequentially as given in the notebook.
- Notebook is commented adequately to give the rational, inferences of the executed code.
