Using TensorFlow to assess bank telemarketing campaign impact

The data-set is related with direct marketing campaigns (were based on phone calls) of a banking institution. Often, more than one contact to the same client was required, in order to access if the product (bank term deposit) would be ('yes') or not ('no') subscribed. The goal is to predict if the client will subscribe a term deposit

Using the bank credit card data we will perform Dimension Reduction and form cluster of data which has similar properties.

Prediction of the churn rate (abandon rate) of clients using Tensor Flow Neural Network

In this project, I built logistic regression model in RStudio to predict the probability of customers enroll in direct payroll deposit so that the bank can save their money and resources by contacting only customers that exhibit high probability and how best the bank can use my logistic regression model to help them strategize business goals.

Build a Model to Predict Whether the client has subscribed a term deposit or not?

Python code to download and parse Community Reinvestment Act disclosures

Classification model to predict if the client will subscribe to a term deposit based on the given bank dataset

Building a logistic regression model

Transforming banking operations with MySQL Bank Management System: robust schema, advanced queries, views, and security measures ensure efficiency and data integrity. Ready to revolutionize the industry.

This repository contains my submission for Task-3 of the Data Science Internship at Prodigy Infotech.

Desafio de data science Semantix