machine learning machine learning (mlteaches machines how to carry out tasks by themselves it is that simple the complexity comes with the detailsand that is most likely the reason you are reading this book maybe you have too much data and too little insightand you hoped that using machine learning algorithms will help you solve this challenge so you started to dig into random algorithms but after some time you were puzzledwhich of the myriad of algorithms should you actually chooseor maybe you are broadly interested in machine learning and have been reading few blogs and articles about it for some time everything seemed to be magic and coolso you started your exploration and fed some toy data into decision tree or support vector machine but after you successfully applied it to some other datayou wonderedwas the whole setting rightdid you get the optimal resultsand how do you know there are no better algorithmsor whether your data was "the right one"welcome to the clubwethe authorswere at those stages once upon timelooking for information that tells the real story behind the theoretical textbooks on machine learning it turned out that much of that information was "black art"not usually taught in standard textbooks soin sensewe wrote this book to our younger selvesa book that not only gives quick introduction to machine learningbut also teaches you lessons that we have learned along the way we hope that it will also give youthe readera smoother entry into one of the most exciting fields in computer science