• Development

Mentors :

• kundeshwar vijay pundalik

• ADRESH ALAGADE

Mentees :

• 20+

We will build Text summarization web app by using Bert model(Hugging Face Transformers). We will deploy this model in two different way one will be by using HTML and other will be Streamlet. Read following content for more information :-
Every day, we are inundated with information. There are numerous articles that we read on a daily basis. As a result, there is a lot of data moving about, largely in the form of text. If we need to learn something about an article, we must read the entire piece to understand it, and many times those articles become excessively long, such as a 5000-word article, which takes a long time. So, in order to receive the useful information contained in 1000 words, we must read the entire 5000-word article, which is a complete waste of time, and if we need to read several articles like that for work purposes, it will take a long time, resulting in a loss of work hour. The goal of text summarizing is to see if we can come up with a method that employs natural language processing to do so. This method will not only save time in comprehending a text, but it will also allow someone to read multiple texts in a short period of time, saving time in the long term.
Objective of Text Summarization:

• Extraction of useful information out of a huge amount of text.
• Reduction of reading time.
• Enable to read more articles as the time for reading each article will be reduced thus gather more information from different articles without losing much time.
• Selecting articles allows one to process more information when reading because only the most significant aspects of the content are captured.

Some useful links :-

• https://github.com/tkmanabat/Text-Summarization.
• https://github.com/dmmiller612/bert-extractive-summarizer.
• https://aws.amazon.com/blogs/machine-learning/part-2-set-up-a-text-summarization-project-with-hugging-face-transformers/
• https://keras.io/examples/nlp/t5_hf_summarization/

We would use Flutter for frontend, Django or NodeJS for backend (a/c to preference of mentees). We would need 2 mentees working on Flutter and 2 mentees working on backend.




Prerequisites: BASIC PYTHON , (HTML OR STREAMLIT) , BASIC KNOWLEDGE OF NEURAL NETWORK, RNN




Note for Mentees:

• Mention whether you want to work on frontend or backend. If you are not clear or want to work on both, mention that.
• If you are good at UI design, write it in proposal

Tentative Timeline :

Week	Work
Week 1-3	EDA and Some other operation (Removal Noise, Lowercase conversion, Tokenization, Stopword Removal, Stemming, lemmatization Removal OOV and Removing Rare word etc.)
Week 4-5	Abstractive Summarization approach(selection of model like which hugging face model is best for text summarization )
Week 6-7	Create model by using model "DistilBART-CNN-12-6" and Write deployment code for streamlet as well as HTML.
Week 8	Final Deployment and Result Analysis.