Linked e-resources
Details
Table of Contents
Intro
Preface
Contents
Editors and Contributors
Introduction to Big Data Analytics
1 Introduction to Big Data
2 The Distinction Between Small and Big Data
3 Classification of Big Data
4 Characteristics of Big Data
5 Who's Generating Big Data?
6 Why Is Big Data Important?
7 Challenges in Big-Data
8 Big Data Applications
9 How Big Data Analysis Differs from Business Intelligence Analysis?
9.1 Business Intelligence
9.2 Big Data
9.3 Differences Between Business Intelligence (BI) and Big Data
10 The Analytical Lifestyle of Big Data
10.1 Phase 1: Discovery
10.2 Phase 2: Data Preparation
10.3 Phase 3: Model Planning
10.4 Phase 4: Model Building
10.5 Phase 5: Communicate Results
10.6 Phase 6: Operationalize
11 Big Data Analysis Necessitates a Set of Skills
12 Big Data Domain
13 Introduction to Big Data Analytics
14 Overview of the Hadoop Ecosystem
14.1 HDFS
14.2 YARN
14.3 MapReduce
14.4 Spark
15 Overview of Big Data Analysis and Its Need
16 Use Cases of Big Data Analytics
17 Challenges in Analyzing Big Data
18 Big Data Quality Dimensions
19 Conclusion
References
DCD_PREDICT: Using Big Data on Prediction for Chest Diseases by Applying Machine Learning Algorithms
1 Introduction
1.1 Introduction
1.2 Background
1.3 Objective
2 Literature Survey
2.1 Summary
3 System Design
3.1 Existing System
3.2 Identification of Common Risks
3.3 Types of Heart Diseases
3.4 Problem Statement
3.5 Scope
3.6 Proposed System
4 Methodology
4.1 Supervised Learning
4.2 Symptom-Based Questionnaire
4.3 Dataset Training and Testing
5 Process and Analysis
5.1 General Process
5.2 Use Case Diagram
5.3 Data Flow Diagram
5.4 System Flow
6 Implementation and Results
6.1 Details of Algorithms
6.2 Data Set and Its Parameters
6.3 Dataset Attributes
6.4 Execution and Screenshots
7 Conclusion and Future Scope
7.1 Conclusion
7.2 Future Scope
References
Design of Energy Efficient IoMT Electrocardiogram (ECG) Machine on 28 nm FPGA
1 Introduction
2 Background
3 Environmental Settings for Energy Efficient IoMT ECG Machine
4 Power Analysis of IoMT ECG Machine
5 Conclusion
References
Automatic Smart Irrigation Method for Agriculture Data
1 Introduction
2 Motivation
3 Contribution of the Chapter
4 Organization and Roadmap of the Article
5 Related Works
6 About the Dataset and Features
7 Methodology and Applied Algorithms
7.1 Data Processing
7.2 Machine Learning
8 Result and Analysis
9 Challenges in Proposed Work
10 Conclusion and Future Work
References
Artificial Intelligence Based Plant Disease Detection
1 Introduction
2 Motivation
3 Contribution of the Chapter
4 Organization of the Chapter
5 Literature Survey
6 Issues and Challenges
7 Methodology
Preface
Contents
Editors and Contributors
Introduction to Big Data Analytics
1 Introduction to Big Data
2 The Distinction Between Small and Big Data
3 Classification of Big Data
4 Characteristics of Big Data
5 Who's Generating Big Data?
6 Why Is Big Data Important?
7 Challenges in Big-Data
8 Big Data Applications
9 How Big Data Analysis Differs from Business Intelligence Analysis?
9.1 Business Intelligence
9.2 Big Data
9.3 Differences Between Business Intelligence (BI) and Big Data
10 The Analytical Lifestyle of Big Data
10.1 Phase 1: Discovery
10.2 Phase 2: Data Preparation
10.3 Phase 3: Model Planning
10.4 Phase 4: Model Building
10.5 Phase 5: Communicate Results
10.6 Phase 6: Operationalize
11 Big Data Analysis Necessitates a Set of Skills
12 Big Data Domain
13 Introduction to Big Data Analytics
14 Overview of the Hadoop Ecosystem
14.1 HDFS
14.2 YARN
14.3 MapReduce
14.4 Spark
15 Overview of Big Data Analysis and Its Need
16 Use Cases of Big Data Analytics
17 Challenges in Analyzing Big Data
18 Big Data Quality Dimensions
19 Conclusion
References
DCD_PREDICT: Using Big Data on Prediction for Chest Diseases by Applying Machine Learning Algorithms
1 Introduction
1.1 Introduction
1.2 Background
1.3 Objective
2 Literature Survey
2.1 Summary
3 System Design
3.1 Existing System
3.2 Identification of Common Risks
3.3 Types of Heart Diseases
3.4 Problem Statement
3.5 Scope
3.6 Proposed System
4 Methodology
4.1 Supervised Learning
4.2 Symptom-Based Questionnaire
4.3 Dataset Training and Testing
5 Process and Analysis
5.1 General Process
5.2 Use Case Diagram
5.3 Data Flow Diagram
5.4 System Flow
6 Implementation and Results
6.1 Details of Algorithms
6.2 Data Set and Its Parameters
6.3 Dataset Attributes
6.4 Execution and Screenshots
7 Conclusion and Future Scope
7.1 Conclusion
7.2 Future Scope
References
Design of Energy Efficient IoMT Electrocardiogram (ECG) Machine on 28 nm FPGA
1 Introduction
2 Background
3 Environmental Settings for Energy Efficient IoMT ECG Machine
4 Power Analysis of IoMT ECG Machine
5 Conclusion
References
Automatic Smart Irrigation Method for Agriculture Data
1 Introduction
2 Motivation
3 Contribution of the Chapter
4 Organization and Roadmap of the Article
5 Related Works
6 About the Dataset and Features
7 Methodology and Applied Algorithms
7.1 Data Processing
7.2 Machine Learning
8 Result and Analysis
9 Challenges in Proposed Work
10 Conclusion and Future Work
References
Artificial Intelligence Based Plant Disease Detection
1 Introduction
2 Motivation
3 Contribution of the Chapter
4 Organization of the Chapter
5 Literature Survey
6 Issues and Challenges
7 Methodology