Last week I started to dig into algorithms. It’s a long and hard way, and I’m struggling a lot.

If you hesitate where to start, I would recommend understanding the basics first. It’s not really about the code — more about math concepts — but this will give you the background that you need, and accidentally you’ll get the whole point of why we should study algorithm.

Yes, I’m talking about the Big O notation.

Wiki says that Big O notation is a mathematical notation that describes the limiting behavior of a function when the argument tends towards a particular value or infinity. Sounds intimidating, right? To put it simply, Big O means a way of comparing code to find out which works the best.

For a programmer, the main goal is to create the fastest and the least memory-intensive code (well, try to create) and Big O is here to the rescue! It helps us to analyze the performance of the code and also allows us to talk formally about the code (don’t forget — communication is a key!).

#data-structures #algorithms #time-complexity #big-o-notation #data-science