Please share the sources or your information. it seems that you are wrong about machine learning, You have classified regression, classification and clustering as not ML, but they are the basis of most ML. NN and SVM both work with these concepts and as I am not very familiar with other terms they may be as well. so, the best classification would be to include regression, classification and clustering as ML and the algorithms as Deep Learning. you may reference MS Learn and the IBM cloud education resources to correct this course. i am very disappointed in this course and believe that a better effort must be put in to ensure current and accurate information. People who are learning for the first time will learn the woncepts wrong.

Hi Balwinder! Thanks for reaching out. Indeed, all coming from academic background, we are advocates of preserving the evolution of the meaning behind the terms used and the disciplines that have appeared over time. Machine learning uses regressions and classification, as you say. But these are statistical phenomena that have been around way earlier than the term "machine learning" came around. Same is valid for the term "algorithm". We do understand the confusion and that's what motivated us to create this Introduction to Data and Data Science course. We would like you to be aware of the terms and buzzwords as they appeared historically to better understand what each discipline is about, as well as why and how we can take advantage of each one of them. If you have other questions you'd like to ask, please don't hesitate to reply to this message or open up a new thread in the Q&A. Thank you! Hope this helps. Kind regards, Martin

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Balwinder Singh Bhandechha

Last answered:

11 Nov 2022

Posted on:

05 Nov 2022

Your inforgraphic is wrong

in Introduction to Data and Data Science / Why do we Need each of these Disciplines?

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Martin Ganchev

Instructor

Posted on:

11 Nov 2022

Your inforgraphic is wrong

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