REVOLUTIONIZING FAKE INSTAGRAM PROFILE DETECTION THROUGH MACHINE LEARNING

The project entails the development of a Python-based system for detecting fake Instagram profiles using machine learning models and image processing techniques. The script employs libraries such as TensorFlow, Keras, Scikit-Learn, Pandas, Matplotlib, Seaborn, and OpenCV, facilitating extensive data handling, statistical analysis, visualization, and machine learning model training. The training dataset is preprocessed and scaled before being fed into a neural network model structured with multiple dense layers and dropout for regularization, optimized using Adam optimizer for categorical crossentropy loss. The model's performance is evaluated using metrics like accuracy and loss progression during training/validation phases.Overall, this project integrates multiple computational techniques to create an automated tool that aids in identifying and analyzing fake profiles on Instagram, showcasing the practical application of AI and machine learning in social media management.