This project is a part of the coursework of Data Mining at Northeastern University, Boston, MA, USA.
H&M is a large fast-fashion retailer company with over 5,000 stores worldwide. Being a large retailer, it is important for H&M to leverage predictive analytics to improve decision-making and operational efficiencies. This project is focused towards helping the marketing team of H&M to help them understand the target customer group for marketing campaigns. The target customer group are the customers that are likely to make a purchase in the next three months. The marketing team can send a customized marketing campaign to the customers who are likely to make a purchase and bolster their revenue.
- Harshit Gaur
- Inferential Statistics
- Machine Learning
- Data Visualization
- Predictive Modeling (Decision Tree, Random Forest, Gradient Boosting, Neural Network, H20 AutoML)
- Python
- Excel, MySql
- Pandas, jupyter, AutoML
- data exploration/descriptive statistics
- data processing/cleaning
- predictive modeling
- writeup/reporting