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Why do this?
Among productivity gurus, there is a term called “flow state.” It happens when you concentrate on what you are doing so hard that you go into some type of a trance. You can’t keep your fingers away from the keyboard. They start working on their accord, producing your best quality code without thinking for hours at a time.
You are doing what’s called “deep work” — a period of time where you are most productive and creative and in the “flow.” The more times you go into a flow during a week, the more high-quality work you produce. The only requirement — no distractions.
Even the smallest stuff such as checking your email, peeking at your notifications, or the most important of all for us programmers — googling something. They are all frictions. They kill creativity and disrupt your thought process. Deep work is like sleep — once you wake up, you can’t just continue where you left off. You have to get back to sleep. Once again.
So, how do you keep distractions, repeated google searches to the minimum? (You can’t eliminate them, unfortunately).
It is simple — you must learn the tools, libraries, and frameworks you need like the palm of your hand.
Today, I rarely go to Sklearn or pandas documentation. I know the structure and API design of these libraries inside out as a user. Even if I forget a class name or a parameter, I know the relevant shortcuts of Jupyterlab and PyCharm that show me what I need in a second.
How did I become this good at these libraries (and many other libraries, for that matter)? I invested quality hours into each, using a proven learning framework I designed. Using it, you can learn any small-to-medium-sized libraries in a few hours or a day or two if the library is humongous (like Tensorflow or NumPy).
Throughout the article, I will outline each step of the framework in detail. By the end, you will have a powerful formula for learning any new package deeply so that you rarely have to go back to the documentation.
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