Machine Learning vs. Deep Learning: What’s the Difference and Why Does it Matter?

At its simplest, machine learning (ML) and deep learning (DP) are both facets of artificial intelligence (AI). To those not in the industry, the terms seem interchangeable, but that’s not quite the case. Deep learning is actually a more advanced, more extensive version of machine learning. To understand further, let’s break down machine learning by itself.

Machine Learning

Machine learning is an application of artificial intelligence that provides systems with the ability to automatically learn and improve from experience and testing, without being explicitly programmed to do so. With ML, computer programs can access data and learn from it themselves. Machine learning involves a lot of complex math and coding, so when we say something is capable of machine learning, we mean that it’s something that can perform a function with provided data and progressively get better over time.

Deep Learning

Deep learning is not wildly different, though its capabilities are. DL imitates the way that the human mind processes information and converts it to knowledge. It’s an important element of data science, which includes statistics and predictive modeling. So how exactly does deep learning work? With the help of a layered structure of algorithms called an artificial neural network. This network is considered the human “brain”. As stated in an article from Zendesk, “It’s a tricky prospect to ensure that a deep learning model doesn’t draw incorrect conclusions—like other examples of AI, it requires lots of training to get the learning processes correct. But when it works as it’s intended to, functional deep learning is often received as a scientific marvel that many consider being the backbone of true artificial intelligence” (Grossfeld, 2020).


The key difference between the two is the differences in performance as the scale of data changes. When a certain data set is small, machine learning is the best fit. But as the data size increases, deep learning becomes necessary because the DL algorithms perform better. This is because a large amount of data is needed for DL to understand and learn from it perfectly.

PSSC Labs has been an expert in the machine learning and deep learning disciplines of computing for 25+ years, providing custom, unique high performance computing solutions to organizations in various industries. To learn how our solutions can help you achieve your business objectives, visit our HPC solutions page and request a quote for your custom system.

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