My Journey To Learn Basics of Artificial Intelligence

“Is calculator Artificial Intelligence?”, “what about a macro in Excel?” , “How does Netflix know which show I want to watch next?”, “What is the difference between Machine Learning and Deep learning?” With these questions in mind, I was looking for a mentor to understand the basics of Artificial Intelligence. Fortunately I met Nitendra, he heads AI Garage in Mastercard and meeting him was an insightful experience.

If you are not a data scientist, don’t want to code but are interested in learning AI concepts & use cases, you may follow my journey. In the end of this article, I will share books I have read and course I am doing.

Sharing my learnings –

Let’s start from a calculator example. What happens when you press 10*3 on a calculator. With a predefined algorithm, calculator converts into binary and multiply based on pre fed logic. That means you have a question and you expect the answer from the calculator. Machine Learning is when you provide the answer and let computer identify the ways to reach without explicit instructions. Let’s say you mention 30 & let computer identify ways to calculate 30. Or you show a picture of a man & let computer identify man or woman or an animal based on various patterns.

Machine learning is to let a machine perform a specific task without using explicit instructions.

So let’s understand machine identifying a difference between a man or woman. Based on few attributes, let’s take a look at below example. Machine identifying pattern in random manner to come up with right solution. If the below pattern gives incorrect answer, it starts again and use different pattern. This continues until it identifies the correct answer.

Deep learning is a subset of Machine learning. An advanced version of Machine learning. Think of a computer with a human like brain. To analyze data with a logic structure similar to how human would draw conclusions. Take the same “Man” example further. Deep learning model would be able to look at the picture and identify “Man with closed eyes”, “Man walking” etc. An average human has 86 billion neurons. Think of these neurons inside human brain as a tree. When we say a word “hello”, multiple neurons communicate to each other inside our brain and a word comes out as “hello”. Deep learning uses the similar neural network logic for machines. Let’s take another example to understand Machine Learning and Deep learning. If you are in a car & you want flashlight to switch on when you say a word “Dark”. Machine learning would be able to recognize with different phrases with word “dark”. A deep learning would go a step further and could be programmed to turn on when it recognizes the audible cue of someone saying the word “dark”. As it continues learning, it might eventually turn on with any phrase containing the word. Now if the flashlight had a deep learning model, it could figure out that it should turn on with the cues “I can’t see”, or the “light switch doesn’t work”, perhaps in tandem with a light sensor. So basically, we are teaching machines to think like human. The challenge is how to teach consciousness to machines. When will machines have morals, ethics and judgement qualities. Let’s take an example from medical field. Machines have already replaced jobs of lab technician by looking at Xray reports identify whether there is tumor or not. But can machine replace judgement of doctors? This is WIP.

If you want to learn AI from scratch, would recommend to do following –

1.       Watch “The Age of AI” series on YouTube originals.

2.       Read a book “Thinking, Fast and Slow” by Daniel Kahneman

3.       Do an online course in Coursera “Deep Learning for Business” by Yonsei University

Let’s learn Artificial Intelligence together!