Retail Insight

• 

  general overview

Inspiration

Helping businesses to grow and thrive.

What it does

This project helps grocery stores predict their sales. It also generates reports for predicting the number of items on their shelves.

How I built it

After browsing several datasets, I have decided to focus on a dataset from Kaggle that allows me to build a generalizable data-driven models for predicting the sales. I performed feature engineering to create more features and utilize a linear regression model for prediction. I also extended the idea for creating plots that helps the businesses predict the number of items on their shelves and estimate the lost demand.

Challenges I ran into

Not having enough time for exploring other ideas that are extensions of this project.

Accomplishments that I'm proud of

This is my first Hackathon experience.

What I learned

Thinking about new ways to apply data analytics skill.

What's next for Retail_Insight

Utilizing the correlation of similar items across different stores for improving the prediction.

Built With

• git
• github
• numpy
• pandas
• python
• scikit-learn
• seaborn