A Step-by-Step Guide to Deploying a Machine Learning Model in a Docker Container

A machine learning model becomes truly valuable when it is deployed beyond the confines of a Jupyter Notebook. In other words, its potential remains untapped unless made accessible to users, enabling them to leverage the model for informed decision-making. Consequently, deploying a machine learning model into production is not just important; it is imperative to unlock its practical utility and bring its benefits to the real world.

Developing and deploying a machine learning model involves various packages and requirements, each …

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