Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough: Volume 4
Gunjan, Vinit Kumar, Zurada, Jacek M., Singh, Ninni
- 出版商: Springer
- 出版日期: 2024-01-14
- 售價: $6,380
- 貴賓價: 9.5 折 $6,061
- 語言: 英文
- 頁數: 342
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3031430085
- ISBN-13: 9783031430084
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相關分類:
Machine Learning
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商品描述
This book provides a systematic and comprehensive overview of cognitive intelligence and AI-enabled IoT ecosystem and machine learning, capable of recognizing the object pattern in complex and large data sets. A remarkable success has been experienced in the last decade by emulating the brain-computer interface. It presents the applied cognitive science methods and AI-enabled technologies that have played a vital role at the core of practical solutions for a wide scope of tasks between handheld apps and industrial process control, autonomous vehicles, IoT, intelligent learning environment, game theory, human computer interaction, environmental policies, life sciences, playing computer games, computational theory, and engineering development.
The book contains contents highlighting artificial neural networks that are analogous to the networks of neurons that comprise the brain and have given computers the ability to distinguish an image of a cat from one of a coconut, to spot pedestrians with enough accuracy to direct a self-driving car, and to recognize and respond to the spoken word. The chapters in this book focus on audiences interested in artificial intelligence, machine learning, fuzzy, cognitive and neurofuzzy-inspired computational systems, their theories, mechanisms, and architecture, which underline human and animal behavior, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step execution and explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions on applications of machine learning, artificial intelligence, and cognitive science such as healthcare products, AI-enabled IoT, gaming, medical, and engineering.
Overall, this book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and academics in the field of machine learning and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.
The book contains contents highlighting artificial neural networks that are analogous to the networks of neurons that comprise the brain and have given computers the ability to distinguish an image of a cat from one of a coconut, to spot pedestrians with enough accuracy to direct a self-driving car, and to recognize and respond to the spoken word. The chapters in this book focus on audiences interested in artificial intelligence, machine learning, fuzzy, cognitive and neurofuzzy-inspired computational systems, their theories, mechanisms, and architecture, which underline human and animal behavior, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step execution and explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions on applications of machine learning, artificial intelligence, and cognitive science such as healthcare products, AI-enabled IoT, gaming, medical, and engineering.
Overall, this book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and academics in the field of machine learning and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.
商品描述(中文翻譯)
本書提供了對認知智能和AI-enabled IoT生態系統以及機器學習的系統性和全面的概述,能夠識別複雜和大型數據集中的物體模式。在過去十年中,通過模擬腦-計算機界面取得了顯著的成功。它介紹了應用認知科學方法和AI-enabled技術,在手持應用程序和工業過程控制、自動駕駛車輛、物聯網、智能學習環境、博弈論、人機交互、環境政策、生命科學、玩電腦遊戲、計算理論和工程開發等廣泛範圍的任務中發揮了核心作用。
本書包含了突出顯示人工神經網絡的內容,這些網絡類似於組成大腦的神經元網絡,使計算機能夠區分出一張貓的圖片和一個椰子的圖片,以足夠的準確性識別行人以引導自駕車,並識別和回應口語。本書的章節專注於對人工智能、機器學習、模糊、認知和神經模糊啟發的計算系統以及它們的理論、機制和架構感興趣的讀者,這些系統強調人類和動物行為,以及它們應用於有意識和智能系統。在當前版本中,它專注於該領域實際應用的成功實施和逐步執行和解釋。它還提供了關於機器學習、人工智能和認知科學應用的廣泛而有啟發性的前沿貢獻,如醫療保健產品、AI-enabled IoT、遊戲、醫學和工程。
總的來說,本書為機器學習和認知科學領域的學生、研究人員、從業人員和學者提供了有價值的有效技術和方法的信息。此外,本書的目的是滿足廣泛範圍的從業人員、學生和研究人員的興趣,他們有興趣在各自的領域應用機器學習和認知科學方法。