Developing an ML model

There are numerous ML models that we interact with on a daily basis as end users, and we likely do not even realize it. Think back to all the activities you did today: scrolling through social media, checking your email, or perhaps you visited a store or a supermarket. In each of these settings, you likely interacted with an already deployed ML model. On social media, the posts that are presented on your feed are likely the output of a supervised recommendation model. The emails you opened were likely filtered for spam emails using a classification model. And, finally, the number of goods available within the grocery store was likely the output of a regression model, allowing them to predict today's demand. In each of these models, a great deal of time and effort was dedicated to ensuring they function and operate correctly. In these situations, while the development of the model is important, the most important thing is how the data is prepared ahead of...