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Applications of Artificial Intelligence and Machine Learning : Select Proceedings of ICAAAIML 2020 / edited by Ankur Choudhary, Arun Prakash Agrawal, Rajasvaran Logeswaran, Bhuvan Unhelkar.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in electrical engineering 1876-1119 ; 778
- Lecture Notes in Electrical Engineering, 1876-1119 ; 778
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Computational intelligence.
- Application software.
- Machine learning.
- Artificial Intelligence.
- Computational Intelligence.
- Computer and Information Systems Applications.
- Machine Learning.
- Local Subjects:
- Artificial Intelligence.
- Computational Intelligence.
- Computer and Information Systems Applications.
- Machine Learning.
- Physical Description:
- 1 online resource (XVI, 738 pages) : 326 illustrations, 247 illustrations in color.
- Edition:
- 1st ed. 2021.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Singapore : Springer Nature Singapore : Imprint: Springer, 2021.
- System Details:
- text file PDF
- Summary:
- The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in healthcare, agriculture, business and security. This volume contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor network, sensors and sensor nodes, software engineering, and image processing. This book will be a valuable resource for students, academics and practitioners in industry working on AI applications.
- Contents:
- Chapter 1: Building a Language Data Set in Telugu Using Machine Learning Techniques to Address Suicidal Ideation and Behaviors in Adolescents
- Chapter 2: Feature Selection and Performance Comparison of Various Machine Learning Classifiers for Analyzing Students' Performance Using Rapid Miner
- Chapter 3: Internet of Things (IoT) Based Automated Light Intensity Model using NodeMcu ESP 8266 Microcontroller
- Chapter 4: Handwritten Mathematical Symbols Classification Using WEKA
- Chapter 5: Enhancing Socio-Cultural Learning Using Hyperlocal Experience
- Chapter 6: Subsequent Technologies behind IoT and its Development Roadmap Towards Integrated Healthcare Prototype Models
- Chapter 7: Bug Assignment- Utilization of Metadata Features along with Feature Selection and Classifiers.
- Other Format:
- Printed edition:
- ISBN:
- 978-981-16-3067-5
- 9789811630675
- Access Restriction:
- Restricted for use by site license.
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