In recent times, there has been an exponential growth of data science and machine learning applications. With the advent of these data-driven applications, python is the go-to choice for most of the developers. In the last few years, python has jumped to the number one position for the languages used for ML which is mostly due to the convenience of packaging the models and exposing them as a service. Model preparation and training is one of many steps in the machine learning lifecycle. Besides an active ML application, there go multiple things that work concurrently under the hood. On a high level, it includes Data cleaning and preparation, selecting and fine-tuning algorithms, model training, delivering the model prediction in the form of an endpoint by exposing an endpoint know as "API".
Oct-18-2020, 18:10:45 GMT