Deep Learning

 

From self-driving cars to large language models, the ability of deep learning to learn from raw data and process large datasets has dramatically broadened the use cases for artificial intelligence. However, like all technologies, deep learning has its own unique limitations and challenges that we will examine in this chapter.

Before we dive in, it’s important to explain the connection between deep learning and machine learning. Machine learning, as discussed, involves algorithms and models that improve with experience and exposure to data. As a subfield of machine learning, deep learning takes the foundational principles of machine learning and applies its own techniques to even larger and more complex datasets. This involves the use of artificial neural networks with deep and multiple layers stacked together to form a model.

While artificial neural networks are not a direct replica of the human brain, (with the human brain estimated to contain 100 billion...