Introduction to Media Summarization

During my academic journey, I have developed a strong foundation in data modeling, statistical analysis, and algorithm design. My final year project, where I developed a robust text summarization application using Django, PyPDF2, and Hugging Face Transformers, is a testament to my ability to apply machine learning techniques to real-world problems. Additionally, I created a video summarization tool using the YouTube Transcript API. These projects not only enhanced my technical skills but also honed my ability to manage projects and deliver solutions that meet user requirements.

Dashboards: To provide users with a comprehensive and intuitive overview of the summarized content, the experimental phase included the development of interactive dashboards. These dashboards offer a centralized platform for users to access and explore the generated summaries, customized according to their preferences. Through visually appealing and user-friendly interfaces, the dashboards present summaries from pdf format as well as Youtube video link. Additionally, users can filter and sort summaries based on criteria such as topics, sources, or relevant time periods, enabling efficient information discovery and analysis.

User Reports: Recognizing the diverse needs of users, the experimental outcomes included the generation of customizable user reports. These reports consolidate summaries from multiple sources and present them in a structured and organized manner, tailored to specific user requirements.