Deep Learning – Short Explanation

When talking about Artificial Intelligence (AI), many other buzzwords and acronyms get thrown around. Two that are often confused are Machine Learning (ML) and Deep Learning. Perhaps a key point to note is that the confusion is very valid as, in reality, deep learning and machine learning are the same. The distinction is that deep learning is a subset of machine learning, but its capabilities and functions are different.

Before we get too far into the weeds, lets break down some of these terms and their purpose in more detail. AI is basically a system that replicates human decision making. ML uses supervised and unsupervised learning to make decisions based on pre-programmed directions. Deep learning uses ML techniques to create connections between different data sets, using logic patterns like humans.

Understanding Deep Learning in the Real World

Deep learning is used in many different ways in the real world. Some examples include price prediction solutions on online websites. For example, if you are attempting to predict the price of an airline ticket, there are certain key facts that need to be understood.

Firstly, you would be looking at the airport you’re flying from and what airport you would like to fly to. Another consideration is the date you are flying on and even the airline and seat type you want. Each of these variables are given a different “weight” and, based on the weighting, a result – in this case price – is provided.

How Deep Learning Works in the World of AI

Deep Learning returned to prominence in recent days when Google’s AlphaGo program managed to defeat Lee Sedol who is one of the highest ranking Go players worldwide. Many of the familiar tools we know from Google, its search engine and voice recognition systems for example use deep learning. In addition, deep learning determines the specific image to pull out of a video sequence to advertise a specific video on YouTube.

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Deep learning as a subset of ML uses a similar sequence when categorizing information. However, its use of an Artificial Neural Network (ANN) makes it significantly more powerful and capable. Many different companies are using deep learning and deep learning techniques already for a variety of different purposes. Some of these applications include fraud detection as well as customer recommendations on a business front. Other companies have focused on using the technology for food and drug preparation as well as image recognition.

A common factor in the application of deep learning is not what is being done but rather the recognition of patterns and similarities in the world around us. Deep learning algorithms are designed to regularly analyze data in a similar fashion to the way humans look at information which is why it will be successful in the future.