Part of the MIT Press Essential Knowledge series, “Machine Learning” has been released in November 2016 and written by Ethem Alpaydin, Professor in the Department of Computer Engineering at Bogaziçi University, Istanbul, author also of widely known “Introduction to Machine Learning”, now in its third edition (MIT Press), on which this new textbook is mainly based.

The MIT Press Essential Knowledge series offers concise, accessible overviews of compelling topics. Written by leading thinkers, the volumes provide expert syntheses of subjects ranging from the cultural and historical to the scientific and technical, “synthesising specialised subject matter for non-specialists”.

As stated by the author, if it is true that today we face big data, “tomorrow’s data will be bigger” and machines need to become more and more intelligent. This is why machine learning – basically computer programs that learn from data -, is becoming such a crucial discipline. If at the beginning computing was just a matter of calculations, now it has moved beyond simple processing and implies also learning. And data science, together with artificial intelligence, is at the very core of it.


The aim of the book is then to provide a comprehensive while concise exposition of machine learning problems and solutions, from the basic of algorithms to some modern applications.

Alpaydin provides a complete but accessible overview of what machine learning is, with no previous technical knowledge required, as only fundamentals are discussed.

“Machine Learning” then includes also a glossary, a further reading part and a specific section approaching future directions for machine learning and data science, discussing some ethical implications as well as legal issues linked to security and privacy.

Within the domain of programming and data science, machine learning is certainly one of the most interesting and challenging topics, considering also its link to computer science, artificial intelligence and (big) data science. Its relevance is going thusly much further the technology or science fields, encompassing many domains of our daily lives, through commercial, behavioural, financial applications, all driven by algorithms. This is why an – at least – basic understanding and awareness of the issue represents nowadays a necessary tool.