August 2023
Intermediate to advanced
144 pages
3h 24m
English
There is a great deal of interesting work happening in data sciences, especially in the realms of Machine Learning (ML) and Deep Learning (DL), and they are popular for good reason. However, the more tried and tested old-timer, mathematical modeling, is not much talked about. Mathematical modeling methods are no less relevant and are complementary to ML. To create successful data products that solve real business problems, we must often deploy the whole breadth of available mathematical tools, far beyond ML.
A model is a simplified representation of a real system and captures the essence of the system. A mathematical model uses variables, operators, functions, equations, and equalities. Under the hood ...
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