The project predicts the sentiment ( positive ,negative, neutral ) on real-time tweets using Tweepy, AWS Kinesis Streaming, S3, Tensorflow Serving, BERT
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Updated
Oct 31, 2022 - Jupyter Notebook
The project predicts the sentiment ( positive ,negative, neutral ) on real-time tweets using Tweepy, AWS Kinesis Streaming, S3, Tensorflow Serving, BERT
The project aims to transform the realm of beauty by developing a sophisticated UNet architecture model where the input represents a woman adorned with makeup, while the output showcases her natural, makeup-free beauty.
This web application classifies potato leaf health by detecting Potato Early Blight, Potato Late Blight, and healthy leaves based on uploaded images. It uses React for the frontend, FastAPI for the backend, and TensorFlow Serving for real-time predictions.
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