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Object detection on images using pretrained models from tensorflow model zoo and draw results on output images.

Emotion Classification is a Natural Language Processing task in Machine Learning where we can process text data and classify into different classes and can detect sentiment of given text.

Optimize tensorflow deep learning models using TensorRT by nvidia to speed up inference of models with good accuracy.

Tensorflow callbacks are very important to customize behaviour of Keras Tensorflow models in training or evaluation. We can either use predefined callbacks from tensorflow or can write our own callbacks to do some process.

Image classification is a very basic example in computer vision yet used widely for a lot of tasks. In image classification, we can input and image to deep learning model and get related label for class which image belongs to. We can use image classification for classifying an object from different classes, checking quality of a manufactured objects(good or not),

Create deep learning models application using flask as web service and deploy to google cloud run using docker and continuous deployment using Github.