Machine learning
Material type:
TextPublication details: Cambridge MIT Press 2021 Description: xix, 255 pISBN: 9780262542524Subject(s): Machine learning | Artificial intelligenceDDC classification: 006.31 Summary: 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 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, 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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Indian Institute of Management LRC General Stacks | IT & Decisions Sciences | 006.31 ALP (Browse shelf(Opens below)) | 1 | Available | 003733 |
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| 006.3028557 DIX Big data analytics using artificial intelligence technologies: | 006.3068 HAQ Enterprise artificial intelligence transformation: a playbook for the next generation of business and technology leaders | 006.31 AGG Machine learning for text | 006.31 ALP Machine learning | 006.31 BRI Real-world machine learning | 006.31 CHE Generalization with deep learning: | 006.31 CLA Mathematics and programming for machine learning with R: |
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 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, 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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