000			02013 a2200241 4500
003			OSt
005			20221114160545.0
008			220603b xxu||||| |||| 00| 0 eng d
020			_a9780262542524
040			_cIIT Kanpur
041			_aeng
082			_a006.31 _bAl74m
100			_aAlpaydin, Ethem
245			_aMachine learning _cEthem Alpaydin
260			_bMIT Press _c2021 _aCambridge
300			_axix, 255p
440			_aThe MIT press essential knowledge series
500			_aRevised and updated edition
520			_aToday, 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 for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of "the new AI." This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias. Alpaydin, an author of a popular textbook on machine learning, explains that as "Big Data" has gotten bigger, the theory of machine learning--the foundation of efforts to process that data into knowledge--has also advanced. He describes the evolution of the field, explains important learning algorithms, and presents example applications. He discusses the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances; and reinforcement learning when an autonomous agent learns to take actions to maximize reward. In a new chapter, he considers transparency, explainability, fairness, and the ethical and legal implications of making decisions based on data.
650			_aMachine learning
650			_aArtificial intelligence
942			_cBK
999			_c565250 _d565250