the amount of digital data in the world has been growing at rate that defies human comprehension the world' data storage capacity has doubled about every three years since the during the time it will take you to read this approximately bits of data will be added to the world' store it' not easy to relate to number that large one way to think about it is that canadian pennies would have surface area roughly twice that of the earth of coursemore data does not always lead to more useful information evolution is slow processand the ability of the human mind to assimilate data hasalasnot doubled every three years one approach that the world is using to attempt to exploit what has come to be known as "big datais statistical machine learning machine learning is hard to define one of the earliest definitions was proposed by the american electrical engineer and computer scientist arthur samuel, who defined it as "field of study that gives computers the ability to learn without being explicitly programmed of coursein some senseevery useful program learns something for examplean implementation of newton' method learns the roots of polynomial humans learn things in two ways--memorization and generalization we use memorization to accumulate individual facts in englandfor exampleprimary school students might learn list of english monarchs humans use generalization to deduce new facts from old facts student of political sciencefor examplemight observe the behavior of large number of politicians and generalize to conclude that all politicians are likely to make decisions intended to enhance their chances of staying in office when computer scientists speak about machine learningthey most often mean the field of writing programs that automatically learn to make useful inferences from implicit patterns in data for examplelinear regression (see learns curve that is model of collection of examples that model can then be used to make predictions about previously unseen examples in generalmachine learning involves observing set of examples that represent incomplete information about some statistical phenomenonand then attempting to infer something about the process that generated those examples the examples are frequently called training data samuel is probably best known as the author of program that played checkers the programwhich he started working on in the and continued to work on into the swas impressive for its timethough not particularly good by modern standards howeverwhile working on it samuel invented several techniques that are still used today among other thingssamuel' checker-playing program was quite possibly the first program ever written that improved based upon "experience