Focused learning is good, but a know-it-all attitude will kill you.
When I started learning data science, I was ready to conquer the world of machine learning, deep learning, and everything in between. Likewise, you got your hands on the latest tools, the hottest tutorials, and a huge stack of math textbooks that could serve as a footstool. But before you dive headfirst into this ocean of knowledge, let me give you some advice: Don’t try to boil the ocean. Or, in simpler terms, don’t strain yourself trying to learn every little thing before you start doing the real work.
The myth of knowing everything
When you learn to drive a car, do you need to understand how the combustion engine works before getting behind the wheel? Do you need to know the precise chemistry of gasoline or the intricate details of tire pressure? No, that’s not the case. You learn the basics – how to use the steering, how to brake, how not to hit that mailbox – and with enough practice it becomes second nature.
The same principle applies to data science. You don’t need to know the inner workings of every algorithm, every statistical theorem, or the entire history of linear algebra to get started. However, many beginners make the mistake of…