You’re probably already very well aware of the terms ‘Data Science (DS)’, ‘Artificial Intelligence (AI)’, ‘Machine Learning (ML)’, and ‘Deep Learning (DL)’. These are used so commonly nowadays, and it’s no surprise, considering how much they have impacted the IT sector.
Over the last couple of years, Artificial Intelligence has been growing rapidly. This can be credited to the fact that several improvements have been made to technology in general, and we now have some extremely powerful computers which can aid the development of AI. The availability of powerful computational systems, higher skill sets, and better knowledge resulted in a sort of AI boom. People could see how much scope the field has, and many of them began to jump on the bandwagon to be a part of this incredible new area of science.
As of now, we have a good mix of levels of expertise. There are those who really know their stuff, who’ve been in the field for almost decades now, and who have made plenty of contributions of their own. There are those who know a good amount, but who are still not quite at an ‘expert’ stage yet. They have a lot more to learn. Finally, there are those who have just taken their first baby steps into this vast industry. These people are still new, and they are yet to learn the fundamental concepts of Artificial Intelligence.
The great thing is, for the second and third groups of people, it may not be so difficult to learn the concepts, since there are so many resources online for such purposes. The only problem here is that they need to be able to find the right materials to learn.
I remember when I started out, I took a while to grasp the fundamentals, mainly due to the fact that I saw so many different definitions, opinions, and explanations everywhere. Everything was so technical and ‘smart-sounding’, but for a newbie like me, I was lost for while.
Thankfully, I managed to understand a lot of the concepts now, and I’m still learning more.
This got me thinking, however, that I should make a cheat sheet for myself. Thus, if at any time I needed to look something up, I’d know a (mostly) reliable source to refer to.
The interesting thing is that a lot of these terms are used widely but defined weakly. This means that for a lot of the terms, there aren’t any actual ‘definitions’, per se. Most of the ones that we have are just concepts that experts, leaders, and random people on the internet tried to elucidate in their own words.
So don’t worry about trying to memorise the definitions. Understanding them and being able to say them in your own words is enough.
That said, let’s understand what these four important words actually mean. After that, we will study their relationship with one another. To make this easier, I have explained the concepts with the help of the simple little cheat sheet given below.
An Artificial Intelligence Cheat Sheet
Data Science (DS):
It is the collection, preparation, and analysis of data, in order to gain some information from it, with the help of many different tools and techniques.
Artificial Intelligence (AI):
It is the ability of machine to think and behave like a human being.
Machine Learning (ML):
It is the process of training a machine to think and behave like a human being.
Deep Learning (DL):
It is a branch of Machine Learning that uses Artificial Neural Networks in order to train a machine to think and behave like a human being.
Let us now take a look at how Data Science, Artificial Intelligence, Machine Learning, and Deep Learning relate to one another.
Deep Learning is a subset of Machine Learning, which is a subset of Artificial Intelligence, which uses Data Science.
Many people get confused by this at first, so here is a slightly more elaborate version of the above statement:
- As shown in the diagram, Deep Learning is a part of Machine Learning. And, Machine Learning is a part of Artificial Intelligence. Therefore, Deep Learning is also a part of Artificial Intelligence.
- There is an intersection between Artificial Intelligence and Data Science, but neither is a subset of the other. In other words, Data Science can be considered as an independent area of study on its own, while also playing a huge role in Artificial Intelligence related research.
- Since Machine Learning and Deep Learning come under the umbrella of Artificial Intelligence, they both require Data Science techniques as well.
That’s about it! Doesn’t seem as difficult as it did before, does it?
Now that you have a better idea of what Data Science, Artificial Intelligence, Machine Learning, and Deep Learning are, and how they relate to each other, it becomes easier to grasp the more advanced concepts. Consider this to be the very first rung of a very long ladder.
All the best!