Predict Whether A Customer Will Be Interested In Buying Travel Insurance

Predict who possible Defaulters are for the Consumer Loans Product

This project develops a predictive model for customer attrition in the telecom industry using advanced machine learning techniques to identify high-risk customers and enable proactive retention strategies.

A microservices-based Streaming and Batch data processing in Cloud Foundry and Kubernetes

This project aims to analyze and visualize customer journeys for Souled Store, providing insights into customer behavior and optimizing the shopping experience. Machine learning was used to predict at what journey stage customer tends to leave their journey with the brand

Brazilian index direction prediction model for the first hour of the day based on Focus reports

Predict survival on the Titanic and get familiar with ML basics

This is the GitHub repository for the technical product documentation for Syncfusion Predictive Analytics components

It contains the necessary code, datasets, and documentation to understand, replicate, and build upon the project's findings and methodologies.

Predicting employee attrition entails gathering historical data on employees, identifying key features, training machine learning models, and deploying them for real-time predictions to aid in retention strategies and organizational stability. Regular monitoring and updates ensure ongoing effectiveness.

A customer segmentation prediction and analysis project with the implementation of RFM analysis and DBSCAN clustering algorithm

This repository focuses on predicting apartment prices and visualizing data related to apartment listings. It combines various datasets to create predictive models and an interactive visualization using D3.js

This repository contains a collection of data science projects which I did during the IBM Data Science Professional certification programme. Each project demonstrates different aspects of data science, data analysis, data visualization and machine learning.

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

Comprehensive analysis of the 2023-24 Premier League season using data-driven insights and predictive models to forecast team standings and player performances, enhancing understanding and enjoyment of the league.

A Bank wants to make use of machine learning to assess the creditworthiness of an applicant by implementing a model that will predict if the potential borrower will default on his/her loan or not, and do this such that they receive a response immediately after completing their application.

A topic designed by Warwick Business School requires students to conduct data mining on the provided data to identify a suitable approach for predicting leads (customers) who will convert and buy the new term deposit.

Data science encompasses a wide range of areas, topics, and sub-domains such as Big Data, Machine & Deep learning (ETL, TensorFlow, Keras), Data Mining/Visualization (EDA), BI, Predictive Analytics, Statistical Analytics, etc.

This project develops a predictive model and a decision support system for evaluating the risk associated with Home Equity Line of Credit (HELOC) applications. It features an interactive interface for financial institutions, integrating multiple models for transparent and effective decision-making.

Development of a monitoring system, that identifies the quality of the printing on the product using the historical vibrational data, quality and production log data.