Best practices in the deployment of AI models

AI model deployment is very important in the life cycle of an AI project. Though AI model is at the core of any AI project, only after the proper deployment the AI model will make true sense. The process of taking a trained ML/AI model and making it's predictions available to the users and other systems is known as "deployment". Let's start from the initiation of an AI project till deployment and look at the best practices in AI model deployment. If a data scientist wants to use scikit-learn models, he just needs to subclass the Model class and implement the necessary methods.