When to use Machine Learning or Deep Learning?

Understanding which AI technologies to use to advance a project can be challenging given the rapid growth and evolution of the science. This article outlines the differences between machine learning and deep learning, and how to determine when to apply each one. In both machine learning and deep learning, engineers use software tools, such as MATLAB, to enable computers to identify trends and characteristics in data by learning from an example data set. In the case of machine learning, training data is used to build a model that the computer can use to classify test data, and ultimately real-world data. Traditionally, an important step in this workflow is the development of features – additional metrics derived from the raw data – which help the model be more accurate.