![]() To that ends, I will explain how to write a program in Python and GNU Octave for a particular task you could classify as data science. If you are already familiar with one of the languages, start with that one and go through the others to look for similarities and differences. To get a feeling for a new programming language (and its documentation), I always start by writing some example programs that perform a task I know well. ![]() eBook: An introduction to programming with Bash.Try for free: Red Hat Learning Subscription. ![]() Discovering new programming styles let me backport some solutions to other languages, and everything became much more interesting. I later studied some other languages, and each one brought some new bit of enlightenment. However, I soon realized that each language was more suitable than others for some applications. Programs became much slower, but I did not have to suffer through writing analysis software. Then a friend suggested I try Python, and life became much easier. Life was hard and dangerous in those years, as I had to manually allocate memory, manage pointers, and remember to free memory. When I started programming, the only language I knew was C. Why? It is mostly a combination of boredom with the old ways and curiosity about the new ways. Choosing Python and GNU Octave for data scienceĮvery so often, I try to learn a new programming language. Some are well-known for solving problems in this space, while others are lesser-known. This article will help you become familiar with doing data science with some popular languages. It is, or it should be, an exercise in clarity.Data science is a domain of knowledge that spans programming languages. Programming is not about which programmer is more clever than the other. You should be able to look at an algorithm and immediately understand what its results will be. You should be able to look at an algorithm and immediatelly deduce its validity, correctness, function, purpose, etc. If I would see someone creating these algorithms, I would tell them that they are far from safe. Of course, the algorithms that the puzzle expects as optimal are unacceptable to me. I depict this answer below, using two images, since it does not fit in one. Where – means move one step, ) means turn clockwise, ( means turn counter-clockwise, and means repeat 4 times what is inside the square brackets. Then the answer to question 6 could be the following: It is interesting to see what the optimal solution for question 6 is, if we consider as optimal solutions not those with the least number of components but those with the least number of bunny steps. But using the solution from question 5 to solve question 4 is far fetched, so I believe that denoting 7 as the compenent number for question 4 is better as it stands. Of course, since question number 4 can also be solved using the solution from question 5, one could argue that question 4 should have the number 6 (instead of 7) for denoting the components needed. The number in each question denotes the minimum mumber of components needed to solve it. From the image below, we can understand that optimal solutions are those which use the least amount of components. The puzzle does not make it clear what considers as optimal solutions. Obviously, the goal is for the bunny to eat all the carrots. This puzzle should have been addressed to adults.īy the way, the answer for question 5 can also be used to solve question 4. Then let the kids give you orders to guide you where they want you to go.īut Google should have never produced such a difficult puzzle meant for kids programming. You can create a floor with square tiles and stand in one. The way kids should learn how to program is exactly like that, though. Today () Google published a doodle that has to do with programming for kids.Īlthough this is the way kids should learn how to program, the doodle is incredibly difficult and should address only seasoned programmers.
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