Is math necessary for data science?

Question

Machine learning

Question date to the Scientists. How much do you need mathematics in order to successfully work in your specialty? and is it really necessary to know the theory at a deep level?
I am now a senior IT engineer in the field of networks, but I would like to change my specialty. Here, in principle, there is also a hell of a theory, and I even taught it, and at one time I knew it very well, but for the most part, it is only needed in order to pass interviews, and I have not interviewed for five years and have forgotten a lot, because in real life there are more work skills are important, i.e. applied skills. Is it the same in data science? Or do you really solve long mats before writing a couple of lines of code. equations?

PS I know Python directly at a good level.

Answer 1

Definitely needed, no options. Moreover, the highest, mathematical analysis, differential calculus, that's all.

Answer 2

Datascience is mathematics.

Answer 3

Everyone expected, but incorrect answer: structures of neural networks, knowledge of Python and Tensorflow ( tutorials ), knowledge of mathematical syntax, mathematical transformations, mathematical analysis.
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Or do you really solve long mats before writing a couple of lines of code. equations?

DS is the analysis of the available input data in order to find an extraction method and then directly extract, from this data, the required target result.
(specially added for "gifted" intellect from birth).
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I will write an example task for DS right away.
There is a wide and deep ditch (it is impossible to get out when falling into it).
There are many short branches and a pond.
You are on the other side, where the branches and the pond.
Task: get over the moat to the opposite edge.
Decide - you can think about DS.
If such tasks confuse you, no matan will help you in solving problems with DS: knowing the formulas you will not be able to apply them to get the desired result.
To say that DS is matan / diffusers / matrices is the same as the question: "what is a lake?" - answer: "depression in the ground, filled with water." That is, without specifics, a puddle, a pool, and a well fit there.
PS: And, as you can see, there are no complicated equations and calculations here.