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sales-forecasting

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Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models

  • Updated Dec 30, 2019
  • Jupyter Notebook

This project focuses on time series forecasting to predict store sales for Corporation Favorita, a large Ecuadorian-based grocery retailer. The goal is to build a model that accurately predicts the unit sales for thousands of items sold at different Favorita stores.

  • Updated Dec 4, 2023
  • Jupyter Notebook

Empower decision-makers with an interactive Power BI dashboard showcasing e-commerce performance metrics and trends. Analyze sales data, forecast future trends, and drive informed strategies for business growth.

  • Updated Jan 8, 2024

Enable stakeholders with an engaging Power BI dashboard illustrating key e-commerce performance indicators and patterns. Evaluate sales data, predict forthcoming trends, and formulate knowledgeable approaches to foster business expansion.

  • Updated Apr 24, 2024

How much camping gear will individual Walmart stores sell each month in a year? To the uninitiated, calculating sales at this level may seem as difficult as predicting the weather. Both types of forecasting rely on science and historical data. While a wrong weather forecast may result in carrying around an umbrella on a sunny day, inaccurate bus…

  • Updated Mar 16, 2020
  • Jupyter Notebook

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