The New: Exploring DL

Difference between ML and DL

Part of our intention with separating ML and DL conceptually in this course is really to create associations in the reader’s mind. For most technical folks in the field, there are specific models and algorithms that come up when we see “ML vs. DL” as a descriptor on a product.

If we ever get confused by the two terms, just remember that DL is a form of ML that’s grown and evolved to form its own ecosystem. Our aim is to demystify that ecosystem as much as possible so that we can confidently understand the dynamics at play with DL products as a product manager.

Artificial neural networks (ANNs)

The foundational idea of DL is centered around our own biological neural networks, and DL uses what’s often the umbrella term of ANNs to solve complex problems. Much of the ecosystem in DL has been inspired by our own brains, where the original neural networks are found. This inspiration comes from the function of the human brain, particularly the idea of learning through examples and its structure as well.

Building blocks of ANNs

Because this isn’t an overly technical course meant for DL engineers, we will refrain from going into the terms and mathematics associated with DL. A basic understanding of an ANN would be helpful, however. ...