Isbn: 9781032944623 - recent advances in deep learning applications: new techniques and practical examples (14 resultados)

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Condición: New. Dr. Uche Onyekpe is a Machine Learning Expert at Ofcom (Office of Communications, UK), where he focuses on developing assessment/audit strategies for AI algorithms used by online platforms such as Instagram, TikTok, and X. He also serves as the Di.

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Hardback. Condición: New. This book presents a collection of rigorously revised papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023). It focuses on deep learning architectures and their applications in domains such as health care, security and threat detection, education, fault diagnosis, and robotic control in industrial environments. Novel ways of using convolutional neural networks, transformers, autoencoders, graph-based neural networks, and large language models for the above applications are covered in this book. Readers will find insights to help them realize novel ways of using deep learning architectures and models in real-world applications and contexts, making this book an essential reference guide for academic researchers, professionals, software engineers in the industry, and innovative product developers. Key Features:Presents state-of-the-art research on deep learningCovers modern real-world applications of deep learningProvides value to students, academic researchers, professionals, software engineers in the industry, and innovative product developers. …

Hardcover. Condición: Brand New. 376 pages. 9.18x6.12x9.45 inches. In Stock.

Hardback. Condición: New. This book presents a collection of rigorously revised papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023). It focuses on deep learning architectures and their applications in domains such as health care, security and threat detection, education, fault diagnosis, and robotic control in industrial environments. Novel ways of using convolutional neural networks, transformers, autoencoders, graph-based neural networks, and large language models for the above applications are covered in this book. Readers will find insights to help them realize novel ways of using deep learning architectures and models in real-world applications and contexts, making this book an essential reference guide for academic researchers, professionals, software engineers in the industry, and innovative product developers. Key Features:Presents state-of-the-art research on deep learningCovers modern real-world applications of deep learningProvides value to students, academic researchers, professionals, software engineers in the industry, and innovative product developers. …

Hardcover. Condición: new. Hardcover. This book presents a collection of rigorously revised papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023). It focuses on deep learning architectures and their applications in domains such as health care, security and threat detection, education, fault diagnosis, and robotic control in industrial environments. Novel ways of using convolutional neural networks, transformers, autoencoders, graph-based neural networks, and large language models for the above applications are covered in this book. Readers will find insights to help them realize novel ways of using deep learning architectures and models in real-world applications and contexts, making this book an essential reference guide for academic researchers, professionals, software engineers in the industry, and innovative product developers. Key Features:Presents state-of-the-art research on deep learningCovers modern real-world applications of deep learningProvides value to students, academic researchers, professionals, software engineers in the industry, and innovative product developers This book presents a collection of extended papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023) and focuses on deep learning architectures and their applications in domains such as healthcare, security, education, fault diagnosis, and robotic control in industrial environments. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condición: new. Hardcover. This book presents a collection of rigorously revised papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023). It focuses on deep learning architectures and their applications in domains such as health care, security and threat detection, education, fault diagnosis, and robotic control in industrial environments. Novel ways of using convolutional neural networks, transformers, autoencoders, graph-based neural networks, and large language models for the above applications are covered in this book. Readers will find insights to help them realize novel ways of using deep learning architectures and models in real-world applications and contexts, making this book an essential reference guide for academic researchers, professionals, software engineers in the industry, and innovative product developers. Key Features:Presents state-of-the-art research on deep learningCovers modern real-world applications of deep learningProvides value to students, academic researchers, professionals, software engineers in the industry, and innovative product developers This book presents a collection of extended papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023) and focuses on deep learning architectures and their applications in domains such as healthcare, security, education, fault diagnosis, and robotic control in industrial environments. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condición: new. Hardcover. This book presents a collection of rigorously revised papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023). It focuses on deep learning architectures and their applications in domains such as health care, security and threat detection, education, fault diagnosis, and robotic control in industrial environments. Novel ways of using convolutional neural networks, transformers, autoencoders, graph-based neural networks, and large language models for the above applications are covered in this book. Readers will find insights to help them realize novel ways of using deep learning architectures and models in real-world applications and contexts, making this book an essential reference guide for academic researchers, professionals, software engineers in the industry, and innovative product developers. Key Features:Presents state-of-the-art research on deep learningCovers modern real-world applications of deep learningProvides value to students, academic researchers, professionals, software engineers in the industry, and innovative product developers This book presents a collection of extended papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023) and focuses on deep learning architectures and their applications in domains such as healthcare, security, education, fault diagnosis, and robotic control in industrial environments. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…