Machine learning and statistics with python

 Introduction: Many times, as a data scientist, you will be working on cloud machines which are on either aws, gcp or something else. These machines are costly, and so when you run your codes on these machines, you are actively increasing the project spending. During my last session in aws, I encountered a moderately large program to run; which according to my estimation would take 48-72 hrs to run. And to decrease the time needed as well as optimize the operations, I took 2 steps. This post will briefly describe these processes. (1) cythonizing my codes: Let's face it. Python is SLOW. yes, python is slow and that's why most of the standard computation libraries are written on cython or c++ background. But being a python and pandas dependent data scientist, I write most of my codes in pure python. These codes, are very slow to run; when let's say compared to c++ or cython equivalent of the same codes. So the easiest way to reduce operation time; is to create cython li...