Deep learning isn’t new but there continues to be confusion around the difference between it and machine learning. We have discussed their similarities and individualities several times in the past, but let’s look at it again. This topic came to us from Analytics Insight in their article, “Understanding Deep Learning Vs. Machine Learning.”
There are many benefits to both technologies, but they do operate differently. Both deep learning and machine learning are considered artificial intelligence (AI). The easiest way to visualize their relationship is as concentric circles with AI — the idea that came first — the largest, then machine learning — which came later, and finally deep learning — fitting inside both.
The key difference between deep learning and machine learning stems from the way data is presented to the system. Machine learning algorithms almost always require structured data, whereas deep learning networks rely on layers of artificial neural networks (ANNs).
Deep learning and machine learning have both been evolving for a while now. Many companies are coming up with innovative deep learning technologies that can solve complicated challenges.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
