Building and Deploying an End-to-End Machine Learning Application with Flask, Angular and Docker

You have created a machine learning model, fine-tuned it and cross-validated over a test set all in notebooks and showed a desired performance. So what’s next? How can you deliver the prediction power of that model to the end users? The answer is simple: integrate your ML model with a frontend app that connects users to your awesome creation.

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