Prediction and Analysis for Knowledge Representation and Machine Learning
暫譯: 知識表示與機器學習的預測與分析
Kumar, Avadhesh, Sagar, Shrddha, Kumar, T. Ganesh
- 出版商: CRC
- 出版日期: 2022-01-31
- 售價: $5,870
- 貴賓價: 9.5 折 $5,577
- 語言: 英文
- 頁數: 248
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 0367649101
- ISBN-13: 9780367649104
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相關分類:
Machine Learning
海外代購書籍(需單獨結帳)
相關主題
商品描述
Number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system's perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems.
Prediction and Analysis for Knowledgeable Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in research filed. The approaches are reviewed by real life examples from a wide range of research topics. An understanding of number of techniques and algorithms that are implemented in knowledge representation in machine learning are available through the book website.
Features:
- Examines the representational adequacy of needed knowledge representation.
- Manipulates inferential appropriateness for knowledge representation in order to produce new knowledge derived from the original information.
- Improving inferential and acquisition efficiency by applying automatic methods to acquire new knowledge.
- Covering the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology.
- Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help human kind, become better and smarter.
This book serves as a reference book for researchers and practitioners who all are working in field of information technology and computer science in knowledge representation in machine learning for basic and advance concepts as well. Now a day it has become very essential to develop adaptive, robust, scalable and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for the industry people and will also help beginners as well as high level users for learning latest things which includes basic and advance concepts.
商品描述(中文翻譯)
目前正在定義多種統計和機器學習的方法。這些方法用於識別系統的過程以及從系統感知數據中創建的模型，幫助科學家生成或改進當前模型。機器學習在科學領域中被廣泛研究，特別是在生物信息學、經濟學、社會科學、生態學和氣候科學中，但對於複雜情境下的數據學習仍需進一步研究。需要先進的知識表示方法來捕捉結構和過程特性，以便為機器學習算法提供有意義的知識。這對於理解困難的科學問題具有重要影響。
《知識表示與機器學習的預測與分析》展示了各種知識表示和機器學習的方法論及架構，這些方法將在研究領域中活躍。這些方法通過來自廣泛研究主題的實際案例進行回顧。書籍網站提供了在機器學習中實施的多種技術和算法的理解。
特色：
- 檢視所需知識表示的表現適當性。
- 操作推理適當性以進行知識表示，從而產生源自原始信息的新知識。
- 通過應用自動化方法來提高推理和獲取效率，以獲取新知識。
- 涵蓋知識表示和機器學習中的主要挑戰、關注點和突破，使用最新技術。
- 描述知識表示及相關技術的理念及其應用，以幫助人類變得更好、更聰明。
本書作為參考書籍，適合所有在信息技術和計算機科學領域從事機器學習中知識表示的研究人員和實踐者，涵蓋基本和進階概念。如今，開發自適應、穩健、可擴展和可靠的應用程序以及設計日常問題的解決方案變得非常重要。這本編輯書籍將對行業人士有所幫助，並將幫助初學者以及高級用戶學習最新的知識，包括基本和進階概念。
作者簡介
Avadhesh Kumar is PVC at Galgotias University, Greater Noida, Uttar Pradesh, India. He has more than 21 years of Academic and Research Experience. He was awarded Ph.D. in Computer Science & Engineering in 2010 from Thapar University, Patiala, Punjab, India. He did his M.Tech. in Information Technology and B.Tech. in Computer Science & Engineering from Harcourt Butler Technological Institute (HBTI), Kanpur, UP, India. His Research Area includes Software Engineering, Aspect-Oriented Software Systems, Component-Based Software Development, Soft Computing, and Artificial Intelligence. He has published more than 30 Research papers in reputed Journals and conferences. He has authored 3 books. He is Reviewer of many International Journals and Conferences. He has been Keynote Speaker in many International Conferences.
Shrddha Sagar is working as Associate Professor in School of Computing Science and Engineering, Galgotias University, NCR Delhi, India. She has completed Ph. D in Computer Science from Banasthali University, Jaipur, India. Her main thrust research areas are Artificial Intelligence, Internet of Things, Machine learning and Big Data. She is a pioneer researcher in the areas of Artificial Intelligence, Internet of Things, Machine learning and has published more than 25 papers in various national / international journals. She has presented paper in National/International Conferences, published book chapters in Taylor & Francis Group (CRC Press), IGI global.
Dr. T. Ganesh Kumar works as an Associate Professor at the School of Computing Science and Engineering in Galgotias University, NCR, Delhi. He received ME degree in Computer Science and Engineering from Manonmaniam Sundaranar University, Tamilnadu, India. He completed his full time PhD degree in Computer Science and Engineering at Manonmaniam Sundaranar University. He was Co-Investigator for two government of India sponsored funded projects He has published many reputed international SCI and Scopus indexed journals and conferences. He is a reviewer of many reputed journals. He has published five patents in India.
Dr. K Sampath Kumar Professor & Research Coordinator in the School of Computing Science and Engineering, Galgotias University, Greater Noida, UP, NCR- Delhi, India. He has complete his Ph.D in Data Mining from Anna University-Chennai, Tamil Nadu, India and obtained his ME from Sathyabama University-Chennai, Tamil Nadu, India. He has over 20 years of teaching and industry experience. His expertise in Big Data, Cloud Computing, IOT, Artificial Intelligence and Real Time Systems. He published more than 50 research articles in the international journals and Conferences and also published 5 patents (IPR).
作者簡介(中文翻譯)
Avadhesh Kumar 是印度北方邦大諾伊達的 Galgotias University 的 PVC。他擁有超過 21 年的學術和研究經驗。他於 2010 年在印度旁遮普邦的 Thapar University 獲得計算機科學與工程的博士學位。他在印度坎普爾的 Harcourt Butler Technological Institute (HBTI) 獲得資訊技術的碩士學位和計算機科學與工程的學士學位。他的研究領域包括軟體工程、面向方面的軟體系統、基於元件的軟體開發、軟計算和人工智慧。他在知名期刊和會議上發表了超過 30 篇研究論文，並著有 3 本書籍。他是多個國際期刊和會議的審稿人，並在多個國際會議上擔任主題演講者。
Shrddha Sagar 擔任印度 NCR 德里 Galgotias University 計算科學與工程學院的副教授。她在印度斌納斯塔利大學獲得計算機科學的博士學位。她的主要研究領域包括人工智慧、物聯網、機器學習和大數據。她是人工智慧、物聯網和機器學習領域的先驅研究者，並在各種國內外期刊上發表了超過 25 篇論文。她在國內外會議上發表論文，並在 Taylor & Francis Group (CRC Press) 和 IGI Global 出版書籍章節。
T. Ganesh Kumar 博士擔任 Galgotias University 計算科學與工程學院的副教授，位於印度 NCR 德里。他在印度泰米爾納德邦的 Manonmaniam Sundaranar University 獲得計算機科學與工程的碩士學位，並在同一所大學完成了計算機科學與工程的全日制博士學位。他曾擔任兩個印度政府資助項目的共同研究者，並在多個知名的國際 SCI 和 Scopus 索引的期刊和會議上發表了許多論文。他是多個知名期刊的審稿人，並在印度獲得了五項專利。
K Sampath Kumar 博士是 Galgotias University 計算科學與工程學院的教授及研究協調員，位於印度北方邦大諾伊達，NCR-德里。他在印度泰米爾納德邦的 Anna University-Chennai 獲得數據挖掘的博士學位，並在 Sathyabama University-Chennai 獲得碩士學位。他擁有超過 20 年的教學和產業經驗，專長於大數據、雲計算、物聯網、人工智慧和即時系統。他在國際期刊和會議上發表了超過 50 篇研究文章，並獲得了 5 項專利 (IPR)。
