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YouTube Transcript Summarization over Flask: This back-end uses Flask framework to receive API calls from the client and then respond with the summarized text response. This API can work only on those YouTube videos which has well-formatted closed captions in it. The same backend also hosts a web version of the Summarizer.
This project aims to classify music genres. CNN architecture and GTZAN dataset were used for model training. Finally, a Web Application was made with Flask.
This Flask Music App is a web application built with Flask that allows users to upload, download, play, and delete songs. It provides a user-friendly interface for browsing and managing a collection of music tracks.
financial manager webapp to manage your deposits and withdrawals and track your transactions and put your wishlist and set a financial target for every month
In this project, sentiment analysis is made from the sentences of the model trained with LSTM and also SMS classification is made with Naive Bayes. Thereafter, a Web Application was made with Flask.