21,69 €
Machine Learning
Machine Learning
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Machine Learning
Machine Learning
El. knyga:
21,69 €
A concise overview of machine learning--computer programs that learn from data--the basis of such applications as voice recognition and driverless cars.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 for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given p…
  • Leidėjas:
  • Metai: 2016
  • Puslapiai: 224
  • ISBN: 9780262337601
  • ISBN-10: 0262337606
  • ISBN-13: 9780262337601
  • Formatas: ACSM ?
  • Kalba: Anglų

Machine Learning (el. knyga) (skaityta knyga) | Ethem Alpaydin | knygos.lt

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A concise overview of machine learning--computer programs that learn from data--the basis of such applications as voice recognition and driverless cars.

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 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 Alpayd�n 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.
Alpayd�n, 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, and fairness, and the ethical and legal implications of making decisions based on data.
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  • Autorius: Ethem Alpaydin
  • Leidėjas:
  • Metai: 2016
  • Puslapiai: 224
  • ISBN: 9780262337601
  • ISBN-10: 0262337606
  • ISBN-13: 9780262337601
  • Formatas: ACSM ?
  • Kalba: Anglų

A concise overview of machine learning--computer programs that learn from data--the basis of such applications as voice recognition and driverless cars.

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 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 Alpayd�n 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.
Alpayd�n, 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, and fairness, and the ethical and legal implications of making decisions based on data.

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