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Deep Learning, Editorial

What is Deep Learning?

Diving into “what is deep learning” while providing an exciting and straightforward introduction to deep learning, how it works, and some example implementations

Author(s): Saniya Parveez, Roberto Iriondo

This tutorial’s code is available on Github and its full implementation as well on Google Colab.

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Introduction

The use of deep learning in real-life applications and research has become crucial during the last decade, for example, with the advancements in image recognition, transfer learning, computer vision, recommendation systems, language understanding, healthcare, machine intelligence, and so on [2] [9].

For example, if you have ever used Facebook to post photos, you may have witnessed how their tech can recognize people in photos. These can be your friends or friends of friends, and in most cases, even if the photo is not clear and blurred, their image recognition software has a high accuracy rate on recognizing the people in them and auto-tagging them [1].

Nevertheless, the applications of deep learning go beyond image recognition. This tutorial will provide a straightforward and basic path to deep learning while explaining how it works, its applications, and its implementations.

Now, let’s dive in!

Figure 1: Artificial intelligence (AI) vs. machine learning (ML) vs. deep learning (DL).

What is Deep Learning?

Deep learning (DL) is a unique subset of machine learning (ML) methodologies using artificial neural networks (ANNs) imperceptibly inspired by the structure of neurons found in the human brain.

In deep learning, the word deep is significant as it refers to the vast amount of layers in the artificial neural…