introduction to machine learning and deep learning of data from the data itself furthermorethey organize concepts as hierarchy where complicated concepts are expressed using primitive concepts the field of deep learning has its primary focus on learning appropriate representations of data such that these could be used to conclude the word "deepin "deep learningrefers to the idea of learning the hierarchy of concepts directly from raw data more technically appropriate term for deep learning would be representation learningand more practical term for the same would be automated feature engineering advances in related fields it is important to note the advances in other fields like compute powerstorage costetc that have played key role in the recent interest and success of deep learning consider the followingfor example the ability to collectstore and process large amounts of data has greatly advanced over the last decade (for instancethe apache hadoop ecosystemthe ability to generate supervised training data (data with labels--for examplepictures annotated with the objects in the picturehas improved lot with the availability of crowd-sourcing services (like amazon mechanical turkthe massive improvements in computational horsepower brought about by graphical processing units (gpusenabled parallel computing to new heights the advances in both the theory and software implementation of automatic differentiation (such as pytorch or theanoaccelerated the speed of development and research for deep learning