Machine learning algorithms and applications Intro Table of Contents Title Page Copyright Acknowledgments Preface Part 1: Machine Learning for Industrial Applications 1 A Learning Based Visualization Application for Air Quality Evaluation During COVID 19 Pandemic in Open Data Centric Services 1.1 Introduction 1.2 Literature Survey 1.3 Implementation Details 1.4 Results and Discussions 1.5 Conclusion References 2 Automatic Counting and Classification of Silkworm Eggs Using Deep Learning 2.1 Introduction 2.2 Conventional Silkworm Egg Detection Approaches 2.3 Proposed Method 2.4 Dataset Generation 2.5 Results 2.6 Conclusion Acknowledgment References 3 A Wind Speed Prediction System Using Deep Neural Networks 3.1 Introduction 3.2 Methodology 3.3 Results and Discussions 3.4 Conclusion References 4 Res SE Net: Boosting Performance of ResNets by Enhancing Bridge Connections 4.1 Introduction 4.2 Related Work 4.3 Preliminaries 4.4 Proposed Model 4.5 Experiments 4.6 Results 4.7 Conclusion References 5 Sakshi Aggarwal Navjot Singh and K.K. Mishra 5.1 Genesis 5.2 The Big Picture: Artificial Neural Network 5.3 Delineating the Cornerstones 5.4 Deep Learning Architectures 5.5 Why is CNN Preferred for Computer Vision Applications 5.6 Unravel Deep Learning in Medical Diagnostic Systems 5.7 Challenges and Future Expectations 5.8 Conclusion References 6 Two Stage Credit Scoring Model Based on Evolutionary Feature Selection and Ensemble Neural Networks 6.1 Introduction 6.2 Literature Survey 6.3 Proposed Model for Credit Scoring 6.4 Results and Discussion 6.5 Conclusion References 7 Enhanced Block Based Feature Agglomeration Clustering for Video Summarization 7.1 Introduction 7.2 Related Works 7.3 Feature Agglomeration Clustering.