Deep Learning: core concepts, methods and apllications
Material type: TextPublication details: Noida Pearson 2022Description: 292.pISBN: 9789356061972Subject(s): Machine learning Deep learning (Machine learning)DDC classification: 006.31 Summary: Pearson presents Deep Learning: Core Concepts, Methods and Applications by globally renowned author and academician, M Gopal. This book explores the theoretical underpinnings of Deep Learning and equips its readers with the knowledge needed to apply powerful deep learning techniques to solve challenging real-world problems. Presented in a non-rigorous mathematical style, the text offers sufficient technical depth to provide working foundation for the subject. The emphasis is on getting the solid grip on core principles and methods. The book shows step-by-step method to conceptualize problems, accurately represent data, select and tune algorithms, interpret and analyse results, and make informed strategic decisions. It also provides platform for hands-on experience through case studies.Features:1.Provides readers with the knowledge of building blocks used in deep learning-based solutions2.Equips learners with the basic domain expertise in applications in image processing, audio signal processing and natural language processing3.Develops learners’ skills to practice software implementation of various algorithms covered in the text4.The reader of this book need not be a professional programmer; only a basic knowledge of Python programming is required for beginners.Item type | Current library | Collection | Call number | Status | Date due | Barcode |
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BK | Kannur University Central Library Stack | Stack | 006.31 GOP/D (Browse shelf (Opens below)) | Available | 59751 |
Pearson presents Deep Learning: Core Concepts, Methods and Applications by globally renowned author and academician, M Gopal. This book explores the theoretical underpinnings of Deep Learning and equips its readers with the knowledge needed to apply powerful deep learning techniques to solve challenging real-world problems. Presented in a non-rigorous mathematical style, the text offers sufficient technical depth to provide working foundation for the subject. The emphasis is on getting the solid grip on core principles and methods. The book shows step-by-step method to conceptualize problems, accurately represent data, select and tune algorithms, interpret and analyse results, and make informed strategic decisions. It also provides platform for hands-on experience through case studies.Features:1.Provides readers with the knowledge of building blocks used in deep learning-based solutions2.Equips learners with the basic domain expertise in applications in image processing, audio signal processing and natural language processing3.Develops learners’ skills to practice software implementation of various algorithms covered in the text4.The reader of this book need not be a professional programmer; only a basic knowledge of Python programming is required for beginners.
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