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Calculus For Data Science: What Do You Really Need to Know?

This one picture shows what areas of calculus and linear algebra are most useful for data scientists.

If you read any article worth its salt on the topic Math Needed for Data Science, you'll see calculus mentioned. Calculus (and it's closely related counterpart, linear algebra) has some very narrow (but very useful) applications to data science. If you have a decent algebra background (which I'm assuming you do, if you're a data scientist!) then you can learn all of the calculus you need in a few hours of study. 

You don't usually need to know exactly how to take derivatives, minimize sums of squares or create clustering algorithms from scratch--there are calculators for that! But if you have a general idea of what's working in the background you'll be able to recognize when results don't make sense or what better alternatives might be available.

References

MATH7502: Mathematics for Data Science 2 (Linear Algebra and Topics...

How Much Math Do You Need to Become a Data Scientist?

Cluster Analysis: Basic Concepts and Algorithms

The Mathematics Behind Principal Component Analysis

Lossy Compression

Fuzzy Relation Calculus in the Compression and Decompression of Fuz...

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Comment by Stephanie Glen on August 12, 2020 at 6:47am

Domingo, I agree, that's a great reason and perhaps warrants a future post on "Why you would want to learn calculus".

Comment by Domingo Cordero on August 6, 2020 at 6:31am

Stephanie, I like your approach, is part of our culture of data scientist, Continue learning for improvement!

Add a reason for learning Calculus ("to recognize when results don't make sense or what better alternatives might be available") 
 moves your post to the next level

regards

Domingo 

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