[Link to project repository]
A machine learning model that performs sentiment analysis on customer feedback using both structured and unstructured data. This project demonstrates NLP techniques and basic ML algorithms for customer insight extraction.
[Link to project repository]
An AI-powered system that predicts customer lifetime value (CLV) while providing interpretable insights into customer behavior. This project showcases predictive analytics and explainable AI techniques for business decision-making.
[Link to project repository]
An advanced analytics system that tracks user behavior across multiple platforms and optimizes pricing strategies in real-time. This project integrates cross-platform data analysis with dynamic pricing algorithms.
[Link to project repository]
A cloud-based machine learning model that predicts customer churn using large-scale data processing. This project demonstrates proficiency in cloud computing and handling big data for predictive modeling.
- Data preprocessing and feature engineering
- Machine learning algorithms relevant to customer behavior
- Natural Language Processing (NLP)
- Time series analysis
- Predictive analytics
- Customer segmentation
- Recommendation systems (as part of user behavior analysis)