Improve marketing campaign of a Portuguese bank by analyzing their past marketing campaign data and recommending which customer to target

The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit.

Machine Learning/Pattern Recognition Models to analyze and predict if a client will subscribe for a term deposit given his/her marketing campaign related data

Use of machine learning to predict whether a customer would subscribe to a term deposit.

Increase the effectiveness of the bank's telemarketing campaign.

Marketing refers to activities undertaken by a company to promote the buying or selling of a product or service. Marketing includes advertising, selling, and delivering products to consumers or other businesses. Our data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone ca…

The main objective is to build a predictive model that predicts whether a new client will subscribe to a term deposit or not, based on data from previous marketing campaigns.

UCI Bank Marketing Machine Learning

These projects as a part of my Data Science internship involve data visualisation, analysis, & prediction using various datasets and machine learning techniques. They utilize libraries like pandas, matplotlib, seaborn, scikit-learn, and NLTK for tasks ranging from gender and age visualisation to sentiment analysis and decision tree classification.

Bank Marketing Prediction using R

The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit (variable y).

This projects explores the bank marketing dataset using automatic EDA packages in R.

bank marketing prediction for a term deposit campaign, identify non-potential customers

This project focuses on predicting customer subscription to term deposits using historical data from direct marketing campaigns. By analyzing features from the dataset, the goal is to develop a predictive model that helps optimize marketing strategies and improve campaign efficiency.

Bank marketing campaign success prediction

Decision Support Software

This repository contains a Python script that analyzes the "Bank Marketing" dataset from the UCI Machine Learning Repository. The primary goal is to predict whether a client will subscribe to a term deposit based on various features using a Decision Tree Classifier.

Binary classification of bank marketing calls to determine the likelihood a customer responds.