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This project involves using deep learning methods like ResNet for deepfake detection.

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DeepFake detection using ResNet

This project marks a significant milestone in my academic journey during my third year (5th semester). It was my first deep dive into developing a sophisticated AI model and working with web technologies. The project involved building a deepfake detection system utilizing the powerful ResNet50 architecture, renowned for its efficiency in image classification tasks.

To bring this concept to life, we integrated Python Flask as the backend framework to create a seamless web application that users could interact with. This experience not only allowed me to gain hands-on expertise in machine learning and deep learning concepts but also taught me the intricacies of deploying AI models into real-world applications.

From training the ResNet50 model on datasets to detect manipulated media, to implementing a functional web interface using Flask, the project encompassed various aspects of full-stack AI development. It was an enriching experience that significantly enhanced my technical skill set, including model optimization, data preprocessing, and integrating AI solutions with web technologies.

This project served as a solid foundation for my future endeavors in artificial intelligence and software development, sparking my passion for creating impactful and innovative technological solutions.

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This project involves using deep learning methods like ResNet for deepfake detection.

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