https://github.com/saravanansuriya/final-retail-sales-forecasting

In this project Utilizing advanced time series forecasting models, successfully predicted department-wide sales for each store for the upcoming year and Visualizing the data in streamlit GUI.
https://github.com/saravanansuriya/final-retail-sales-forecasting

data-wrangling eda model-building pandas python-script streamlit-webapp

Last synced: about 1 month ago
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In this project Utilizing advanced time series forecasting models, successfully predicted department-wide sales for each store for the upcoming year and Visualizing the data in streamlit GUI.

• Host: GitHub
• URL: https://github.com/saravanansuriya/final-retail-sales-forecasting
• Owner: SaravananSuriya
• Created: 2024-01-18T11:27:50.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-02-25T08:27:59.000Z (11 months ago)
• Last Synced: 2024-02-25T09:29:56.305Z (11 months ago)
• Topics: data-wrangling, eda, model-building, pandas, python-script, streamlit-webapp
• Language: Jupyter Notebook
• Homepage:
• Size: 4.8 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Final-Retail-Sales-Forecasting

**Capstone Final Project assigned by Guvi**

**Linkedin URL:** https://www.linkedin.com/in/saravanan-b-241468269/details/projects/

**Project title:** Final-Retail-Sales-Forecasting

**Skills take away From This Project:** Python scripting, Data Wrangling, EDA, Model Building, Streamlit.

**Domain:** upermarkets, Chain and Convenience Stores.

**Dataset Link:** [Dataset](https://drive.google.com/drive/folders/1-DX3a7-jraKDIPhJY1HNBSt5E4sA5hmb)

**Problem Statement:** Predict the department-wide sales for each store for the following year and the Model effects of markdowns on holiday weeks.

**Results:** In this project Utilizing advanced time series forecasting models, successfully predicted department-wide sales for each store for the upcoming year. The forecasting model considered historical sales data, seasonality patterns, and other relevant factors to provide accurate and reliable predictions