Demystifying Artificial Intelligence, Data Science, Machine Learning, Deep Learning for Beginners!

Hello World!

Hope you are enjoying working from home!

In my association with multiple online/offline edu-tech's where I have been teaching many data science aspirants across the globe, One question which keeps popping up now and then is, "What is the difference between Data Science and Machine Learning? Artificial Intelligence and ML? Deep Learning and ML? or many such permutations and combinations that you can think of".

The answer is more of a perspective than an objective, but a few perspectives are always stronger than others. I decided to put my understanding into demystifying these terms with the help of a human experience analogy. 

Here we go!

Artificial Intelligence

Let me start with one of the most enticing words in today's era, i.e. Artificial Intelligence(AI). There are two words here, 'ARTIFICIAL' and 'INTELLIGENCE'. First, what is Artificial? Something which is not NATURAL (Let's say here natural is HUMAN). So, if 'Natural' is to 'Human', then 'Artificial' is to the 'MACHINE'. Now coming to the second word, INTELLIGENCE. What is it? According to Wikipedia, Intelligence is the capacity for logic, understanding, self-awareness, learning, emotional knowledge, reasoning, planning, creativity, critical thinking, and problem-solving. So, are we(HUMANS) intelligent? Well! That's debatable! Hahaha…. Alright Alright! I accept. Humans are intelligent. And when we want to mimic that intelligence into something that is not natural, it is called Artificial Intelligence. Now there are various aspects of that intelligence which we will discuss some other day. Today, we aim to build an analogy between Artificial Intelligence and Human Intelligence. We will try to understand all the terms while doing that.

Data

What makes humans intelligent? Are we born intelligent? Let me tell you a story. When I was a kid, I touched a fire that burnt my finger. That incident made me INTELLIGENT enough not to make the same mistake again. (That's exactly how I became smart enough to walk, to talk, to understand, to decide, to write this article, etc.). It is THE EXPERIENCE which made us all intelligent. Now, if you want to make a machine intelligent, how will you give it the same experience? You cannot expect the machine to go and touch the fire and realise the outcome. So, what is the solution? That's where DATA comes in. Humans record their experiences in the form of data. The machine uses this data to become intelligent similar to humans using experience to become intelligent.

Machine Learning

Now, to experience that fire incident, there was a procedure involved. 1. I saw the fire. 2. I moved towards it. 3. Then I extended my hand towards the fire. 4. I touched the fire. 5. Fire burnt my fingers. 6. My senses were activated. 7. The burning sensation and pain made me remove my hands in briskly. So, I went through a process of burning my fingers before I learned something from that experience. So, If we need a machine to learn from the data, it also requires a process, and we all know that there is a specific name given to the PROCESS in the computer science field, i.e. ALGORITHM. So, the steps which machines follow to learn from the data are called MACHINE LEARNING ALGORITHMS or simply MACHINE LEARNING.

The machine uses a MACHINE LEARNING algorithm to learn from DATA to become ARTIFICIALLY INTELLIGENT.

Data Science

Going back to the fire story, there was more to it than just a process(ALGORITHM) and experience(DATA). I saw the fire. I visualise it; it was reddish yellow. I heard the sound of flames. The point is there were many attributes of the fire and surrounding which I processed in my mind and saved for future reference. We unconsciously understand and analyse these attributes/variables while experiencing anything and everything. Machines also need a way to process the data and extract information from the different attributes. The science of dealing with data to process it, understand it, and extract information from it comes under the umbrella of DATA SCIENCE. This part is crucial as we know that there are many types of data and various ways to handle it (We will discuss the data some other day).

So this is it! We covered everything. Thank you...

Oh, wait! I forgot one more word, "DEEP LEARNING". Well, it is just another machine-learning algorithm inspired by the design of neurons in the human brain (Only if we really understood the human brain ;) ). Don't hate me if I am oversimplifying this, but YES, it is just another algorithm. The only difference is that it is way more complex and powerful than other conventional algorithms and has solved multiple problems which seemed impossible a few years back.

So, to reiterate:

The machine uses a MACHINE LEARNING algorithm to learn from DATA using DATA SCIENCE methodologies to become ARTIFICIALLY INTELLIGENT.

Hope this article gave you a holistic picture of all these terminologies popping up in today's technology world!

Please share your feedback and let me know if you want me to write other concepts with similar human analogies.

Thank you!