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Understanding deep learning

Publisher: London The MIT Press, 2023Description: xvi, 527 p. ; ill. (some col.), 24 cm.ISBN: 9780262048644.Subject(s): Machine learning | Computer Vision | Fully connected network | Loss function | Q-learning | Reinforcement learning | Stochastic gradient descent | Supervised learningDDC classification: 006.31 Summary: This book covers modern deep learning and tackles supervised learning, model architecture, unsupervised learning, and deep reinforcement learning.

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Item type	Current location	Call number	Status	Date due	Barcode
Books	DAU	006.31 PRI (Browse shelf)	Checked out	15/12/2025	035393

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Previous	006.31 NOW Advanced structured prediction	006.31 PED Deep learning : concepts and architectures	006.31 PLA Deep reinforcement learning	006.31 PRI Understanding deep learning	006.31 RAE Logical and relational learning	006.31 RAF Inside Deep Learning : Math, Algorithms, Models	006.31 RAS Machine learning with PyTorch and Scikit-Learn : develop machine learning and deep learning models with Python	Next

Includes bibliographical references and index.

This book covers modern deep learning and tackles supervised learning, model architecture, unsupervised learning, and deep reinforcement learning.

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