This is a complete Machine Learning based Web Application designed to detect fake or "bot" profiles on Instagram. Built using Python, Flask, and Scikit-Learn, this project analyzes user profile data (such as profile picture, bio length, follower ratio, etc.) to predict if an account is Real or Fake.
This is a high-demand project perfect for students, developers, or researchers looking for a ready-to-deploy Machine Learning solution.
What is Included?

• Complete Source Code: Python scripts for the model and Flask web app.
• Trained Model: Pre-trained machine learning model ready for predictions.
• Dataset: The CSV dataset used for training.
• Project Documentation: A professional project report and synopsis (PDF/Docx) explaining the system design and algorithms.
• Installation Guide: Step-by-step instructions to run the project.

High Accuracy: Uses advanced ML algorithms trained on a large dataset.

Built with Flask and HTML/CSS for easy user interaction.
Instant results upon entering data.
Graphs and charts to visualize the dataset (optional feature in code).
Works on desktop and mobile browsers.

python 3.7 or higherPIP (Python Package Manager)Libraries: Flask, Pandas, Numpy, Scikit-learn, Pickle

Download and unzip the project file.Open the terminal/command prompt in the project folder.Install dependencies: pip install -r requirements.txtRun the application: python app.pyOpen your browser and go to <a href="http://127.0.0.1:5000">http://127.0.0.1:5000</a> to test the detector.