Applications of artificial intelligence and machine learning : select proceedings of ICAAAIML 2020

Applications of artificial intelligence and machine learning : select proceedings of ICAAAIML 2020 / Ankur Choudhary, Arun Prakash Agrawal, Rajasvaran Logeswaran, Bhuvan Unhelkar, editors.

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...

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Bibliographic Details
Corporate Author: International Conference on Advances and Applications of Artificial Intelligence and Machine Learning Greater Noida, India
Other Authors: Choudhary, Ankur (Editor), Agrawal, Arun Prakash (Editor), Logeswaran, Rajasvaran (Editor), Unhelkar, Bhuvan (Editor)
Format: eBook
Language:English
Published: Singapore : Springer, [2021]
Series:Lecture notes in electrical engineering ; v. 778.
Subjects:
Artificial intelligence > Congresses.
Artificial intelligence
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
Online Access:Click for online access
Table of Contents:
  • Intro
  • ICAAAIML-2020
  • Preface
  • Contents
  • About the Editors
  • Artificial Intelligence and Its Applications in Smart Education
  • Building a Language Data Set in Telugu Using Machine Learning Techniques to Address Suicidal Ideation and Behaviors in Adolescents
  • 1 Introduction
  • 2 Suicidal Data Set Creation in Telugu
  • 3 Technique Used for Data Gathering to Create Required Data Set
  • 4 Data Collection
  • 4.1 Scrapping
  • 4.2 Cleaning
  • 4.3 Annotation
  • 4.4 Data Set Statistics
  • 5 Methodology
  • 6 Experiments and Results
  • 6.1 Accuracy by ML Classifiers
  • 6.2 Binary Classification Measures
  • 7 Conclusion
  • 8 Future Work
  • References
  • Feature Selection and Performance Comparison of Various Machine Learning Classifiers for Analyzing Students' Performance Using Rapid Miner
  • 1 Introduction
  • 2 Literature Review
  • 3 Research Methodology
  • 4 Experiment and Results
  • 5 Conclusion
  • References
  • Internet of Things (IoT) Based Automated Light Intensity Model Using NodeMcu ESP 8266 Microcontroller
  • 1 Introduction
  • 1.1 Problem Statement
  • 1.2 Objectives
  • 2 Research Methodology
  • 3 Literature Survey
  • 4 Performance Analysis
  • 4.1 Analysis Outcomes
  • 5 Conclusion and Future Scope
  • References
  • Handwritten Mathematical Symbols Classification Using WEKA
  • 1 Introduction
  • 2 Literature Review and Related Work
  • 3 Proposed Work
  • 4 Implementation
  • 5 Conclusion and Future Scope
  • References
  • Enhancing Sociocultural Learning Using Hyperlocal Experience
  • 1 Introduction
  • 2 Literature Survey
  • 3 Working of the System
  • 3.1 Overview
  • 3.2 Hyperlocal Forecasting
  • 3.3 Architecture
  • 3.4 Methodology
  • 3.5 Proposed Solution
  • 3.6 Algorithm
  • 4 Conclusion
  • 5 Future Enhancements
  • References
  • Subsequent Technologies Behind IoT and Its Development Roadmap Toward Integrated Healthcare Prototype Models
  • 1 Introduction
  • 2 Technologies Behind IoT
  • 2.1 IoT Development Boards and IoT Hardware
  • 2.2 IDE (Integrated Development Environment)
  • 2.3 Protocols
  • 2.4 Network Spine
  • 2.5 Internetwork Cloud Stages/server
  • 2.6 Software
  • 3 IoT Gateway Device
  • 4 IoT Development Roadmap and Healthcare Prototype
  • 5 Conclusion
  • References
  • Big Data and Data Mining
  • Bug Assignment-Utilization of Metadata Features Along with Feature Selection and Classifiers
  • 1 Introduction
  • 2 Literature Survey
  • 3 Proposed En-TRAM Triager
  • 4 Experimental Setup and Results
  • 4.1 Experiment Setup
  • 4.2 Results
  • 5 Conclusion
  • References
  • Role of Artificial Intelligence in Detection of Hateful Speech for Hinglish Data on Social Media
  • 1 Introduction
  • 1.1 Previous Work
  • 2 Corpus Creation and Annotation
  • 2.1 Annotations
  • 3 Methodology
  • 3.1 Bidirectional Encoder Representations from Transformers (BERT)
  • 3.2 Embeddings from Language Models (ELMo)
  • 3.3 Flair
  • 4 System Design
  • 4.1 Data Pre-Processing
  • 4.2 Fine-Tuning Approaches
  • 5 Results and Discussion

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