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Final year college project, based on Digital Image Processing, Computer Vision and Deep Learning. It is aimed towards helping visually impaired people to access digital media and information of their surrounding, through text recognition and objection classification.
First end-to-end ML project developed in PyCharm, using the Kaggle car prices dataset. The objective is to develop a basic model from scratch using a custom environment, build an API, deploy and use it for predictions.
This project is designed to classify the sentiments of the real-time Tweets fetched via Twitter API. Implemented in an end-to-end manner deployed using Flask Framework in Heroku Platform(PAAS).
Successfully established an image classification model using PyTorch to classify the images of several distinct natural sceneries such as mountains, glaciers, forests, seas, streets and buildings with an accuracy of 86%.