Sinposis

TODAY, MACHINE LEARNING UNDERLIES A RANGE OF APPLICATIONS WE USE EVERY DAY, FROM PRODUCT RECOMMENDATIONS TO VOICE RECOGNITION_AS WELL AS SOME WE DON'T YET USE EVERYDAY, INCLUDING DRIVERLESS CARS. IT IS THE BASIS OF THE NEW APPROACH IN COMPUTING WHERE WE DO NOT WRITE PROGRAMS BUT COLLECT DATA; THE IDEA IS TO LEARN THE ALGORITHMS FOR THE TASKS AUTOMATICALLY FROM DATA. AS COMPUTING DEVICES GROW MORE UBIQUITOUS, A LARGER PART OF OUR LIVES AND WORK IS RECORDED DIGITALLY, AND AS "BIG DATA" HAS GOTTEN BIGGER, THE THEORY OF MACHINE LEARNING_THE FOUNDATION OF EFFORTS TO PROCESS THAT DATA INTO KNOWLEDGE_HAS ALSO ADVANCED. IN THIS BOOK, MACHINE LEARNING EXPERT ETHEM ALPAYDIN OFFERS A CONCISE OVERVIEW OF THE SUBJECT FOR THE GENERAL READER, DESCRIBING ITS EVOLUTION, EXPLAINING IMPORTANT LEARNING ALGORITHMS, AND PRESENTING EXAMPLE APPLICATIONS.