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.

A machine learning project that analyzes bank marketing campaigns and predicts customer responses to term deposit offers using data-driven insights.

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.

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 to a term deposit (variable y).

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 campaign success prediction

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.

End-to-end machine learning project to predict customer subscription to bank marketing campaigns using ANN and classical ML models (Logistic Regression, Random Forest, XGBoost). Includes EDA, preprocessing, class imbalance handling, hyperparameter tuning, and model comparison using ROC-AUC.

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

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

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.