Predictive Analysis for Big Mart Sales Using Machine Learning Algorithms | Python IEEE Project

Predictive Analysis for Big Mart Sales Using Machine Learning Algorithms | Python Final Year Project.
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?Project Title: Predictive Analysis for Big Mart Sales Using Machine Learning Algorithms.
?Implementation Code: Python.
?Algorithm / Model Used: Decision Tree Regression.
?Web Framework: Flask.
?️Frontend: HTML, CSS, JavaScript.
?Cost (In Indian Rupees): Rs.3000/.

IEEE Base paper Abstract:
Currently, supermarket run-centres, Big Marts keep track of each individual item's sales data in order to anticipate potential consumer demand and update inventory management. Anomalies and general trends are often discovered by mining the data warehouse's data store. For retailers like Big Mart, the resulting data can be used to forecast future sales volume using various machine learning techniques like big mart. A predictive model was developed using Xgboost, Linear regression, Polynomial regression, and Ridge regression techniques for forecasting the sales of a business such as Big -Mart, and it was discovered that the model outperforms existing models.

REFERENCE:
Ranjitha P, Spandana M, “Predictive Analysis for Big Mart Sales Using Machine Learning Algorithms”, IEEE Conference, 2021.

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