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.

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…

Trained a model that estimates if a lead is likely to be converted based on lead behavior in historical customer data using ML.

Bu proje, Global AI Hub ve Akbank iş birliğiyle düzenlenen Makine Öğrenimine Giriş Bootcamp kapsamında geliştirilmiştir.

Bank Marketing Data Set Binary Classification in python

Bank Marketing Prediction using R

Machine learning project predicting bank term deposit subscriptions using customer demographics and campaign data. Features multiple ML models (Random Forest, Logistic Regression, Decision Tree), SMOTE for class balancing, and interactive Streamlit app for real-time predictions.

Fortivus is a machine learning project that uses Logistic Regression to analyze real bank marketing data. It predicts whether a customer will subscribe to a term deposit, supporting smarter marketing strategies and data‑driven decisions.

Analyzing user data to predict their choice of enrolling in a term deposit. Deriving insights from the data to target customers during marketing.

Bank Marketing Data Set

This is a Effectiveness Prediction Machine Learning project based on Classification problem

Bank marketing prediction with Logistic Regression (SMOTE, L1/L2) and Electrical Grid Stability classification with SVM (Linear, RBF, Polynomial). Achieved 97.3% accuracy with tuned RBF kernel.

Using classification to predict whether the customer will subscribe to the bank's term deposit or not

Use a PyTorch dense-net to predict if a client subscribes to a term deposit

Decision Support Software

A bank deposit prediction (deep learning) project from my MSc Data Science course

This repository will compare the performance of different classification algorithms on various imbalanced datasets using multiple balancing techniques.

Analysis on bank marketing campaign dataset: client demographics, product holdings, loan status, campaign effectiveness, and customer conversion for term deposits using Python (data cleaning, EDA, modeling).

End-to-end ML project predicting term deposit subscriptions using bank marketing data.