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MACHINE-LEARNING Project

Superstore Sales and Profit Prediction Final Year Project Source Code

Get runnable Superstore Sales and Profit Prediction Final Year Project Source Code with database files, project setup instructions, live demo options and installation support. This project resource helps students understand the implementation, modules, workflow and technical architecture of a complete MACHINE-LEARNING project.

Superstore Sales and Profit Prediction Final Year Project preview

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What's Included in Your Download

  • Complete Source Code

    Runnable project code with frontend & backend.

  • Database Files

    SQL database file and required resources.

  • Setup Instructions

    Step-by-step README and project setup guide.

  • Configuration Files

    All configuration files and dependencies included.

  • Module Explanation

    Understand key modules and project workflow.

  • Setup & Demo Support

    Installation help and live demo where available.

Choose the Package That Fits You Best

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01 Source Code Only

₹99

One-time Payment

  • Complete project source code
  • Database / data resources
  • Dependencies & configuration
  • README / setup guide
  • Instant download access
Download — ₹99
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02 Code + Setup Support

₹248

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  • Everything in Source Code plan
  • Remote setup assistance
  • Database & configuration setup
  • Run verification
  • Help via WhatsApp / Email
Download — ₹248

Project's Overview

Superstore Sales and Profit Prediction is a full-stack Python Flask based final year project developed for predicting sales and profit using the Superstore dataset. This major project includes user management, dataset management, CSV upload, dataset preview, data cleaning, filters, machine learning model training, prediction forms, bulk CSV prediction, business insights, training history, prediction history, and admin management. Users can sign up, log in, manage profile, recover passwords through email and security question, upload datasets, select dataset versions, preview data with search/sort, clean missing values and duplicates, apply filters, train Random Forest models, predict sales and profit, and view prediction history. Admin users can manage users and clean datasets. This Superstore Sales and Profit Prediction source code is suitable for students who need a final year project, major project, minor project, source code, and project report based on Flask, pandas, scikit-learn, SQLite, and machine learning.

Login Credentials

Admin Account

Demo User Account

Other dummy users:
Any seeded dummy user can be used with the default user password if available in the seed data.

Project Features and Functionality

Live Demo Preview the working project.