Fake Instagram Profile Detector is a machine learning web application built with Python and Flask for analyzing Instagram profile data and predicting whether an account is real or fake.

The application uses profile-related information such as profile picture data, bio length, follower ratios, and other available profile attributes as inputs for its prediction process.

The package includes the complete Python source code, a trained machine learning model, the dataset used for training, and project documentation explaining the system and algorithms.

The Flask-based web interface provides a simple way to enter profile information and receive prediction results. The project also includes optional graphs and charts for visualizing dataset information.

It is designed as a ready-to-run machine learning project for students, developers, and researchers interested in Python, Flask, data science, and machine learning applications.

• Machine learning-based fake profile detection

• Predicts whether a profile is real or fake

• Python and Flask web application

• Profile data analysis for prediction

• Trained machine learning model included

• Training dataset included

• Complete Python source code

• Project report and synopsis included

• Installation guide included

• Flask-based web interface

• HTML/CSS user interface

• Instant prediction results after entering data

• Optional graphs and charts for dataset visualization

• Desktop browser support

• Mobile browser support

• Scikit-Learn based machine learning implementation

• Python 3.7 or higher

• PIP (Python Package Manager)

• Flask

• Pandas

• NumPy

• Scikit-Learn

• Pickle

• A compatible environment for running a Python Flask application

• Web browser for accessing the local application