Deep Learning Python Tensorflow 2 Flask ResNet50 CNN ZMQ Runtime Performance Free Guided Project Speed up the web app Optimization Low-Latency App Performance Improvement

Welcome to the project on How to build low-latency deep-learning-based flask app. In this project, we will refactor the entire codebase of the project [ How to Deploy an Image Classification Model using Flask][1]. That monolithic code will be refactored to form two microservices - the flask service and model service. The model service acts as a server that renders pretrained Tensorflow model as a deep learning API, and keeps listening for any incoming requests. The flask service requests the model service, and displays the response from the model server. This way, we write cleaner code and promote service isolation.

Further …