Group academic research project predicts bank client term deposit subscriptions using data science and machine learning, with a deployed application for real-time predictions through streamlit

"Bank Marketing Term Deposit Prediction: A classification project using machine learning algorithms to predict whether a customer will subscribe to a term deposit based on demographic and financial data. Aim: Develop a model to improve marketing strategies and increase subscription rates."

A project focused on predicting bank term deposit subscriptions using classification models. The repository contains data analysis, feature engineering, and model implementation steps aimed at maximizing prediction accuracy.

A machine learning API built using FastAPI to predict customer subscription to long-term deposits based on marketing campaign data. This project preprocesses input data, trains models, and serves predictions through a RESTful API.

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.

Term Deposit Subscription Prediction using Ensemble Techniques

Project related to term deposit subscription prediction

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This project predicts whether a client will subscribe to a term deposit using the Portuguese Bank Marketing dataset, a widely used benchmark for binary classification tasks.

Bank Term Deposit Subscription Prediction | ML Classification Project

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ML Bank Marketing Prediction - Term Deposit Subscription Predictor Project

This project develops a machine learning classification system to predict whether a bank customer will subscribe to a term deposit product (YES / NO) based on telemarketing campaign data.

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The Project is based on term deposit subscription prediction using different machine learning algorithms

This repository contain project "Term Deposit Subscription Prediction". Where I predicted the probability if a client will subscribe to term deposit or not.

Capstone Project 17.1 – Comparing Classifiers for Bank Term Deposit Subscription Prediction | Berkeley ML & AI Professional Certificate

Term Deposit Subscription Prediction This project is a Flask-based Machine Learning Web Application that predicts whether a client will subscribe to a term deposit based on demographic, financial, and campaign-related details.

Term Deposit Subscription Prediction: A machine learning project using the Bank Marketing dataset to predict whether clients will subscribe to a term deposit. Includes data preprocessing, EDA, model building, and evaluation to optimize marketing strategies and improve conversion rates.

Hi, I'm Ganesh 👋 Aspiring Data Scientist | Machine Learning | Generative AI Featured Projects • Customer Churn Prediction • Bank Term Deposit Subscription Prediction Using Machine Learning • AI Chatbot using LLMs • Power BI Dashboard

ML project using Random Forest for classification (term deposit subscription) and regression (balance prediction) on bank marketing data. Includes preprocessing, feature selection, model tuning, and joblib model saving.

This project involves the analysis of bank marketing campaigns and the prediction of term deposit subscriptions. By utilizing machine learning techniques, we aim to uncover patterns in customer behavior and predict whether a client will subscribe to a term deposit based on various features.

💰 An end-to-end machine learning project to predict bank term deposit subscriptions. Includes a Jupyter Notebook for detailed EDA and model training, and a Streamlit app for interactive predictions.

The Term Deposit Prediction Project involves developing an artificial neural network (ANN) model to predict whether clients will subscribe to a term deposit offered by a Portuguese bank. By analyzing client attributes and past marketing campaign data, this project aims to enhance the bank's marketing strategy and improve subscription rates.

A Term Deposit Subscription Prediction Project is a classification problem that aims to predict whether a customer will subscribe to a term deposit based on their demographic, behavioral, and financial information. This type of project is typically built using machine learning models to help financial institutions improve their marketing campaigns.

# 📊 Customer Subscription Prediction - Machine Learning Model ## 📝 Project Overview This project builds a **machine learning model** to predict whether a customer will subscribe to a term deposit based on their demographic, financial, and economic data.

Project Title: Bank Marketing Predictive Analysis. In this project, Built a predictive model to forecast term deposit subscriptions for a Portuguese bank. Employed Python, Scikit-Learn, and data preprocessing techniques for accurate predictions, showcasing data science expertise.

This project performs customer subscription prediction using the Bank Marketing dataset. It involves data preprocessing, encoding categorical features, normalization, and model training using the Gaussian Naive Bayes classifier to predict whether a customer will subscribe to a term deposit.

This project predicts customer subscription to term deposits in a bank marketing campaign using Logistic Regression, Random Forest, and SMOTE to handle class imbalance. It demonstrates key steps in data preprocessing, model building, and evaluation to improve prediction performance.