What is AI and how is it related to Data Science and Machine Learning
With the booming opportunities in the field of AI, everyone resembles to be buzzing around three words AI, Data Science and Machine Learning. For everyone moving into the field, it appears all of the three words somewhat stand for the same thing but truly it’s not. Job titles like Data Scientist, Machine Learning Engineer or an AI Engineer are very lucrative in 2020. But people who crave to transition into this field gets confused during the initial phase of their transition as all three words are mostly use at the same place but they fail to realize that all the three job profiles — Data Scientist, Machine Learning Engineer and AI Engineer or Expert, have different responsibilities.
What is Artificial Intelligence?
In generalize, terms AI is giving a machine the ability to work like a human brain. Some of the traits of a human mind include logical reasoning, learning and self-correction. Normally machines do as they are told. They don’t know anything else besides what they are programmed for and the task that they have to execute. Allowing the machines to think like a human brain is a big leap in technology because now they can improve by themselves through learning.
Artificial Intelligence can be divided into two:
- Narrow AI: It deals with a specific implementation of AI, only allowing the AI to improve and perform well on a specific task with a lot of constraints.
- Artificial General Intelligence: It is something scientists dream of, that is a human-level intelligent AI implementation where the computer or the machine is able to deal with problems without any constraints like a human brain.
What is Data Science?
Data Science as the name suggests has to do a lot with data. Data Science is the field that deals with getting insights from the available data. With the increase in the use of the internet and everything going digital from e-commerce to restaurant booking. There is an exponential growth in the amount of data that is now available.
Below is the growing trend of data from 2010 to 2025 where one zettabyte(ZB) is equal to a trillion Gigabyte (gb)
This large chunk of data includes the number of items bought per day on Amazon, most sold items in the month, details about the item sold in a particular part of the world similarly the news data, whether data and the list never stops.
For enterprises and researchers, this enormous amount of data is very useful. As it can help answer a lot of questions. This is where Data Science steps in. It helps us to get insight from the available data. We get the insight after processing, pattern recognition, cleaning and visualization of the data. Data Science does not deal with training a model that work is done by the Machine Learning Engineer from the data that they receive from Data Scientists.
What is Machine learning?
Machine Learning(ML) is about the ability of a machine to learn from its environment. It deals more with algorithms than data. Efforts are put in by Machine Learning Engineers to build these algorithms, tweak already built algorithms and use them on the data provided by the Data Scientists to train a model. In layman terms, by training a model we mean using the data to educate the machine and tell it what to do and what not to do. For example, Machine Learning Engineer shows the machine 100 photos of a dog and 100 of cat and teaches it using the algorithms that this is how a cat and a dog look like.
Then they show the machine a totally new photo of a dog that it has never seen before and asks it to tell whether it’s a dog or cat. Based on the answer the Machine Learning engineer concludes a rating for the machine and algorithm that how good was the machine able to learn which is called the learning rate.
How the three are interrelated and conclusion
Below is a graph that shows how the three are interrelated. Machine learning is a complete subset of AI while Data Science is only a partial subset of AI and ML.
AI is addressing the whole technology in general terms. Machine Learning is a part of the whole tech that is allowing the machines to learn through algorithms and Data Science on the other side acts as a helping hand for Machine Learning Engineers to help them execute their task.
I hope I was able to draw a line that was easy to understand, between the three: Artificial Intelligence, Data Science and Machine Learning
