Market Segmentation Flask Web Architecture

A web application built using Flask for market segmentation using unsupervised machine learning algorithms. The application allows users to upload a dataset, select relevant features, and apply clustering algorithms to group similar customers based on their purchasing behavior.

By: @anuj_dwivedi

Getting Started

Prerequisites

Running the Application

  1. Clone this repository
  2. Install the prerequisites mentioned above
  3. Open a terminal and navigate to the root directory of the project
  4. Run the following command to start the Flask application: python app.py
  5. Open a web browser and go to http://localhost:5000

Architecture

The web application is built using Flask, a Python web framework. The user interface is designed using HTML/CSS/JavaScript, and the server-side scripts are written in Python. The data processing is done using Pandas, and the machine learning algorithms are implemented using Scikit-learn.

Algorithm

The web application implements the K-means clustering algorithm for market segmentation. K-means is an unsupervised machine learning algorithm that groups similar data points together based on their features. It is widely used for customer segmentation in marketing.

Contributors

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