Fundamentals and Methods of Machine and Deep Learning. Pradeep Singh
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12 8 Machine Learning and Deep Learning for Medical Analysis—A Case Study on Heart Disease Data 8.1 Introduction 8.2 Related Works 8.3 Data Pre-Processing 8.4 Feature Selection 8.5 ML Classifiers Techniques 8.6 Hyperparameter Tuning 8.7 Dataset Description 8.8 Experiments and Results 8.9 Analysis 8.10 Conclusion References
13 9 A Novel Convolutional Neural Network Model to Predict Software Defects 9.1 Introduction 9.2 Related Works 9.3 Theoretical Background 9.4 Experimental Setup 9.5 Conclusion and Future Scope References
14 10 Predictive Analysis of Online Television Videos Using Machine Learning Algorithms 10.1 Introduction 10.2 Proposed Framework 10.3 Feature Selection 10.4 Classification 10.5 Online Incremental Learning 10.6 Results and Discussion 10.7 Conclusion References
15 11 A Combinational Deep Learning Approach to Visually Evoked EEG-Based Image Classification 11.1 Introduction 11.2 Literature Review 11.3 Methodology 11.4 Result and Discussion 11.5 Conclusion References
16 12 Application of Machine Learning Algorithms With Balancing Techniques for Credit Card Fraud Detection: A Comparative Analysis 12.1 Introduction 12.2 Methods and Techniques 12.3 Results and Discussion 12.4 Conclusions References
17 13 Crack Detection in Civil Structures Using Deep Learning 13.1 Introduction 13.2 Related Work 13.3 Infrared Thermal Imaging Detection Method 13.4 Crack Detection Using CNN 13.5 Results and Discussion 13.6 Conclusion References
18 14 Measuring Urban Sprawl Using Machine Learning 14.1 Introduction 14.2 Literature Survey 14.3 Remotely Sensed Images 14.4 Feature Selection 14.5 Classification Using Machine Learning Algorithms 14.6 Results 14.7 Discussion and Conclusion Acknowledgements References
19 15 Application of Deep Learning Algorithms in Medical Image Processing: A Survey 15.1 Introduction 15.2 Overview of Deep Learning Algorithms 15.3 Overview of Medical Images 15.4 Scheme of Medical Image Processing 15.5 Anatomy-Wise Medical Image Processing With Deep Learning 15.6 Conclusion References