Project Info:

• A product recommender system which suggests relevant items based on users' purchase pattern and provide attractive offers.

• Tested among a group of 60 users' and observed an 35% increased click-through rate.

• Worked on RFM clustering using K-means.

• Implemented using Python, Flask, Pandas, scikit-learn, NumPy and Cassandra.

• Used Future Groups dataset for Big Data Analysis.

Project Details:

• Technologies:iOS, HTML5, CSS3, PHP, Java
• Packages and Libraries used:NumPy, pandas, Matplotlib, seaborn, jinja2.
• Github:https://github.com/revathynarayanan98/ProximityMarketing