machine learning and python the dream team the goal of machine learning is to teach machines (softwareto carry out tasks by providing them with couple of examples (how to do or not do tasklet us assume that each morning when you turn on your computeryou perform the same task of moving -mails around so that only those -mails belonging to particular topic end up in the same folder after some timeyou feel bored and think of automating this chore one way would be to start analyzing your brain and writing down all the rules your brain processes while you are shuffling your -mails howeverthis will be quite cumbersome and always imperfect while you will miss some rulesyou will over-specify others better and more future-proof way would be to automate this process by choosing set of -mail meta information and body/folder name pairs and let an algorithm come up with the best rule set the pairs would be your training dataand the resulting rule set (also called modelcould then be applied to future -mails that we have not yet seen this is machine learning in its simplest form of coursemachine learning (often also referred to as data mining or predictive analysisis not brand new field in itself quite the contraryits success over recent years can be attributed to the pragmatic way of using rock-solid techniques and insights from other successful fieldsfor examplestatistics therethe purpose is for us humans to get insights into the data by learning more about the underlying patterns and relationships as you read more and more about successful applications of machine learning (you have checked out kaggle com alreadyhaven' you?)you will see that applied statistics is common field among machine learning experts as you will see laterthe process of coming up with decent ml approach is never waterfall-like process insteadyou will see yourself going back and forth in your analysistrying out different versions of your input data on diverse sets of ml algorithms it is this explorative nature that lends itself perfectly to python being an interpreted high-level programming languageit may seem that python was designed specifically for the process of trying out different things what is moreit does this very fast sure enoughit is slower than or similar statically-typed programming languagesneverthelesswith myriad of easy-to-use libraries that are often written in cyou don' have to sacrifice speed for agility [