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  3. Machine learning

Patterns, Predictions, and Actions

- Foundations of Machine Learning
Af: Benjamin Recht, Moritz Hardt Engelsk Hardback

Patterns, Predictions, and Actions

- Foundations of Machine Learning
Af: Benjamin Recht, Moritz Hardt Engelsk Hardback
Tjek vores konkurrenters priser
An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impactsPatterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actionsPays special attention to societal impacts and fairness in decision makingTraces the development of machine learning from its origins to todayFeatures a novel chapter on machine learning benchmarks and datasetsInvites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebraAn essential textbook for students and a guide for researchers
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Tjek vores konkurrenters priser
An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impactsPatterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actionsPays special attention to societal impacts and fairness in decision makingTraces the development of machine learning from its origins to todayFeatures a novel chapter on machine learning benchmarks and datasetsInvites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebraAn essential textbook for students and a guide for researchers
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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 320
ISBN-13: 9780691233734
Indbinding: Hardback
Udgave:
ISBN-10: 069123373X
Kategori: Machine learning
Udg. Dato: 18 okt 2022
Længde: 27mm
Bredde: 262mm
Højde: 184mm
Forlag: Princeton University Press
Oplagsdato: 18 okt 2022
Forfatter(e): Benjamin Recht, Moritz Hardt
Forfatter(e) Benjamin Recht, Moritz Hardt

Kategori Machine learning

ISBN-13 9780691233734

Sprog Engelsk

Indbinding Hardback

Sider 320

Udgave

Længde 27mm

Bredde 262mm

Højde 184mm

Udg. Dato 18 okt 2022

Oplagsdato 18 okt 2022

Forlag Princeton University Press

Kategori sammenhænge