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Machine Learning Approach for Cloud Data Analytics in IoT
Читать книгу Machine Learning Approach for Cloud Data Analytics in IoT - Группа авторов - Страница 1
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Страница 1
Table of Contents
Guide
List of Illustrations
List of Tables
Pages
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1
Machine Learning–Based Data Analysis
1.1 Introduction
1.2 Machine Learning for the Internet of Things Using Data Analysis
1.2.1 Computing Framework
1.2.2 Fog Computing
1.2.3 Edge Computing
1.2.4 Cloud Computing
1.2.5 Distributed Computing
1.3 Machine Learning Applied to Data Analysis
1.3.1 Supervised Learning Systems
1.3.2 Decision Trees
1.3.3 Decision Tree Types
1.3.4 Unsupervised Machine Learning
1.3.5 Association Rule Learning
1.3.6 Reinforcement Learning
1.4 Practical Issues in Machine Learning
1.5 Data Acquisition
1.6 Understanding the Data Formats Used in Data Analysis Applications
1.7 Data Cleaning
1.8 Data Visualization
1.9 Understanding the Data Analysis Problem-Solving Approach
1.10 Visualizing Data to Enhance Understanding and Using Neural Networks in Data Analysis
1.11 Statistical Data Analysis Techniques
1.11.1 Hypothesis Testing
1.11.2 Regression Analysis
1.12 Text Analysis and Visual and Audio Analysis
1.13 Mathematical and Parallel Techniques for Data Analysis
1.13.1 Using Map-Reduce
1.13.2 Leaning Analysis
1.13.3 Market Basket Analysis
1.14 Conclusion
References
Страница 45
2
Machine Learning for Cyber-Immune IoT Applications
2.1 Introduction
2.2 Some Associated Impactful Terms 2.2.1 IoT
2.2.2 IoT Device
2.2.3 IoT Service
2.2.4 Internet Security
2.2.5 Data Security
2.2.6 Cyberthreats
2.2.7 Cyber Attack
2.2.8 Malware
2.2.9 Phishing
2.2.10 Ransomware
2.2.11 Spear-Phishing
2.2.12 Spyware
2.2.13 Cybercrime
2.2.14 IoT Cyber Security
2.2.15 IP Address
2.3 Cloud Rationality Representation 2.3.1 Cloud
2.3.2 Cloud Data
2.3.3 Cloud Security
2.3.4 Cloud Computing
2.4 Integration of IoT With Cloud
2.5 The Concepts That Rules Over 2.5.1 Artificial Intelligent
2.5.2 Overview of Machine Learning
2.5.2.1 Supervised Learning
2.5.2.2 Unsupervised Learning
2.5.3 Applications of Machine Learning in Cyber Security
2.5.4 Applications of Machine Learning in Cybercrime
2.5.5 Adherence of Machine Learning With Cyber Security in Relevance to IoT
2.5.6 Distributed Denial-of-Service
2.6 Related Work
2.7 Methodology
2.8 Discussions and Implications
2.9 Conclusion
References
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Employing Machine Learning Approaches for Predictive Data Analytics in Retail Industry
3.1 Introduction
3.2 Related Work
3.3 Predictive Data Analytics in Retail
3.3.1 ML for Predictive Data Analytics
3.3.2 Use Cases
3.3.3 Limitations and Challenges
3.4 Proposed Model
3.4.1 Case Study
3.5 Conclusion and Future Scope
References
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