
Sách keo gáy, bìa mềm
This book focuses on deep learning (DL),
which is an important aspect of data science, that includes predictive
modeling. DL applications are widely used in domains such as finance,
transport, healthcare, automanufacturing, and advertising. The design of
the DL models based on artificial neural networks is influenced by the
structure and operation of the brain. This book presents a comprehensive
resource for those who seek a solid grasp of the techniques in DL.
Key features:
Provides knowledge on theory and design of state-of-the-art deep learning models for real-world applications
Explains the concepts and terminology in problem-solving with deep learning
Explores the theoretical basis for major algorithms and approaches in deep learning
Discusses the enhancement techniques of deep learning models
Identifies the performance evaluation techniques for deep learning models
Accordingly,
the book covers the entire process flow of deep learning by providing
awareness of each of the widely used models. This book can be used as a
beginners’ guide where the user can understand the associated concepts
and techniques. This book will be a useful resource for undergraduate
and postgraduate students, engineers, and researchers, who are starting
to learn the subject of deep learning.
Categories:Computers - Artificial Intelligence (AI)
Content Type:Books
Year:2023
Edition:1
Language:english
Pages:199