A Simple Way to Understand Machine Learning Vs. Deep Learning

Ashish Kumar
Sep 4, 2018 · 2 min read

Artificial Intelligence is currently the fastest growing fields and rapid strides being made in this field can often leave people confused and overwhelmed. However, it is not that hard to comprehend if you realize that it in fact comes down to two concepts you are most probably familiar with- machine learning and deep learning. Often it is seen that these concepts are used in a way that gives an impression that they are one and the same. However, these two terms most closely associated with AI are different and it is important that you find yourself capable of comprehending the difference between the two, more so in the light of the fact that these two concepts are increasingly being put into practice by corporations around the world.

In the following sections we shall delve a bit deeper to get a better grasp of these two concepts synonymous with artificial intelligence.

Machine learning: What is it?

A simple definition of machine learning would be:

An algorithm that analyses data, make sense of that data and then put into practice the knowledge derived to make wise and astute decisions.

Machine learning powers a lot of automated tasks spread across different industry verticals and sectors like entertainment, data security, financial services, etc. Designed to work like virtual assistants, machine language involves a lot of complex coding and mathematics. In other words when we say that something possesses ‘machine learning’ capabilities, it simply means that it performs function based on the data that it is provided with. For example, it could be intelligent lighting system in your house which would turn itself off when the word’ dark’ or similar phrase containing ‘dark’ is uttered by you.

Deep learning vs. machine learning

To put it bluntly, deep learning is a part of machine learning. It is the reason it is often used interchangeably with machine learning despite the fact that it comes equipped with its own set of unique abilities. Machine learning models need human intervention if a machine learning algorithm fails to make accurate prediction. On the other hand, algorithms in deep learning model are capable on their own of determining the accuracy of their prediction.

In other words, deep learning simulates the working of a human brain. Enabling it accomplish the task is a structured layer of algorithms called an artificial neural network (ANN) that can make well-informed decisions on its own.

Machine learning and deep learning is the backbone of artificial intelligence. And with the huge popularity that AI commands and the critical role it is going to play in future, people who know machine learning programs can reap immense rewards for their talent.