The Basics of Machine Learning Modeling

It can be difficult to see how machine learning (ML) affects the daily lives of ordinary people. In fact, ML is everywhere! In the process of searching for a restaurant for dinner, you almost certainly used ML. In the search for a dress to wear for a dinner party, you would have used ML. On your way to your dinner appointment, you probably used ML as well if you used one of the ride-sharing apps. ML has become so widely used that it has become an essential part of our lives, although it is usually unnoticeable. With ever-growing data and its accessibility, the applications and needs for ML are rapidly rising across various industries. However, the pace of the growth in trained data scientists has yet to meet the pace of growth ML needs in businesses, despite abundant resources and software libraries that make building ML models easier, due to the fact that it takes time and experience for a data scientist and ML engineer to master such skill sets.

In this article, we will cover the following topics:

• Key ML tasks and applications
• Steps in building ML models

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