The Subtle Differences among Data Science, Machine Learning, and Artificial Intelligence
What is Data Science and why is it important? How is it related to Machine Learning? Are Machine Learning and Artificial Intelligence the same thing? If no, how are they different?
I encounter these and similar questions very frequently by a lot of people excited to enter this amazing field which has suddenly grown so much.
Data Science is anything that you do with Data. Data gathering, storing, cleaning, processing, analyzing, visualizing, etc. all come under the term DATA SCIENCE. As a data scientist should be able to play around with data of any size and different types, build scalable tools to get insights, and simply, answer questions which will drive business value. This includes the use of advanced analytics, statistics, and often times, coding.
Machine Learning means making the machines learn with help of data. So how do you get this data and convert it into the right form for the machine to learn from it? DATA SCIENCE!
Artificial Intelligence is a broader concept of making the machines intelligent. It means making machines capable of doing things which are done easily by humans, like cognitive thinking. ML, we can say, is a part of AI, or is the major part of AI. Because how do you make the machines learn like humans? MACHINE LEARNING!
Now the main question arises: Why are these such buzzwords?
Because we have so much data about everything today, that almost all business decisions can be based on it. The combined power of cognitive thinking like humans and computational capabilities of computers is bound to disrupt virtually everything!
Image credits:
in-post image 1: freepik
in-post image 2: markcarrigan
in-post image 3: Emily Barry
in-post image 4: TowardsDataScience
Astrophysics Research Software Engineer | Building anything and everything in between Data Analysis and UI Design | GSoC Mentor
6 年This a wonderful article. Much needed!
Machine Learning and Data Scientist
6 年"Data Science is anything that you do with Data"... :-( ...This is just plain wrong.? Comments like this are a common misunderstanding amongst people less familiar with this field, and they are a significant problem for those of us who do work in this area.? Creating expectations around our role which are as massively broad as this just sets data scientists up to fail.?A data scientist has enough stuff already that they need to be up to speed with just to do their day job, without being tasked with all an encompassing?requirement such as this.? I would also argue, wrt your Venn diagram, that machine learning is actually a defining component of data science ( or alternatively that DS is *applied* machine learning).? ?Data science which does not contain machine learning I would typically refer to as data analysis.?
CVML, perception, robotics and MLOps
6 年Tanmayan Pande
Entrepreneur, Investor and Technology Strategist
6 年I am not sure the Venn diagram to differentiate between Data science, ML and AI is correct, actually it is misleading.
Senior Manager, Advanced Analytics @ CIBC | Queen's Alumni | Professor, Artificial Intelligence @ SETAS, Centennial College | Microsoft Certified | Machine Learning | Natural Language Processing |
6 年Good Article, but I disagree with the line. Data Science is anything that you do with Data. There is a lot of work in Data Analysis, which is often correlated with Business Intelligence and Business Analysis. Any sort of Data Analysis without statistical inference, exploratory and advanced analytics cant be termed as Data Science.? I believe that Data Science can more closely be related to preprocessing of data - detecting and correcting outliers, applying transformations to the data in order to normalize it, Handling Categorical and non categorical features