Right now, OTUS is opening a set for a new stream of the advanced course "Mathematics for Data Science" , in this regard, we would like to invite you to a free webinar , in which our expert, Petr Lukyanchenko, will tell you in detail about the course program, and also answer your questions ...
βIs it really necessary to understand the math behind machine learning algorithms? Python already has a ton of widely available libraries that you can easily use to build models! "
I've heard this from hobbyist data scientist more than once. This misconception is far more prevalent than we would like, and continues to give rise to naive fantasies among aspiring data professionals.
Let's make this clear once and for all - to become a data scientist you need to understand the math behind machine learning algorithms. This is an integral part of the Data Scientist's role and every recruiter and machine learning expert will attest to this.
So how do we learn this? Well, that's exactly what I want to talk to you about today. This article outlines the various aspects of mathematics you need to know to fully master machine learning, including linear algebra, probability theory, and more.
At what level do you need to understand math to be competent in machine learning?
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