• Prof Arti Devmane
• Yash Mangesh Kalekar
• Manish Pandurang Warghade
• Magesh kadam

The PDF Summarizer project pioneers an automated approach to summarizing PDF documents by integrating Natural Language Processing (NLP) and OpenAI's advanced language models. In today's data-rich environment, the challenge of efficiently extracting insights from PDF documents underscores the need for innovative solutions. Combining NLP techniques with OpenAI's language models, the PDF Summarizer system adeptly interprets the semantics, context, and sentiment of textual content within PDFs to generate concise summaries. Through advanced machine learning algorithms, it empowers users with actionable insights, revolutionizing information retrieval and decision-making processes across diverse domains. This paper presents the methodology, implementation, and evaluation of the PDF Summarizer project, demonstrating its potential to transform how we engage with PDF documents in the digital era.

Natural language processing (NLP), OpenAI

"TEXT AND PDF SUMMARIZER USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.82-87, June-2024, Available :http://www.jetir.org/papers/JETIRGH06013.pdf

"TEXT AND PDF SUMMARIZER USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pp82-87, June-2024, Available at : http://www.jetir.org/papers/JETIRGH06013.pdf