Advanced Analytics and Deep Learning Models. Группа авторов

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      1  Cover

      2  Title Page

      3  Copyright

      4  Preface

      5  Part 1: Introduction to Computer Vision 1 Artificial Intelligence in Language Learning: Practices and Prospects 1.1 Introduction 1.2 Evolution of CALL 1.3 Defining Artificial Intelligence 1.4 Historical Overview of AI in Education and Language Learning 1.5 Implication of Artificial Intelligence in Education 1.6 Artificial Intelligence Tools Enhance the Teaching and Learning Processes 1.7 Conclusion References 2 Real Estate Price Prediction Using Machine Learning Algorithms 2.1 Introduction 2.2 Literature Review 2.3 Proposed Work 2.4 Algorithms 2.5 Evaluation Metrics 2.6 Result of Prediction References 3 Multi-Criteria–Based Entertainment Recommender System Using Clustering Approach 3.1 Introduction 3.2 Work Related Multi-Criteria Recommender System 3.3 Working Principle 3.4 Comparison Among Different Methods 3.5 Advantages of Multi-Criteria Recommender System 3.6 Challenges of Multi-Criteria Recommender System 3.7 Conclusion References 4 Adoption of Machine/Deep Learning in Cloud With a Case Study on Discernment of Cervical Cancer 4.1 Introduction 4.2 Background Study 4.3 Overview of Machine Learning/Deep Learning 4.4 Connection Between Machine Learning/Deep Learning and Cloud Computing 4.5 Machine Learning/Deep Learning Algorithm 4.6 A Project Implementation on Discernment of Cervical Cancer by Using Machine/Deep Learning in Cloud 4.7 Applications 4.8 Advantages of Adoption of Cloud in Machine Learning/ Deep Learning 4.9 Conclusion References 5 Machine Learning and Internet of Things–Based Models for Healthcare Monitoring 5.1 Introduction 5.2 Literature Survey 5.3 Interpretable Machine Learning in Healthcare 5.4 Opportunities in Machine Learning for Healthcare 5.5 Why Combining IoT and ML? 5.6 Applications of Machine Learning in Medical and Pharma 5.7 Challenges and Future Research Direction 5.8 Conclusion References 6 Machine Learning–Based Disease Diagnosis and Prediction for E-Healthcare System 6.1 Introduction 6.2 Literature Survey 6.3 Machine Learning Applications in Biomedical Imaging 6.4 Brain Tumor Classification Using Machine Learning and IoT 6.5 Early Detection of Dementia Disease Using Machine Learning and IoT-Based Applications 6.6 IoT and Machine Learning-Based Diseases Prediction and Diagnosis System for EHRs 6.7 Machine Learning Applications for a Real-Time Monitoring of Arrhythmia Patients Using IoT 6.8 IoT and Machine Learning–Based System for Medical Data Mining 6.9 Conclusion and Future Works References

      6  Part 2: Introduction to Deep Learning and its Models 7 Deep Learning Methods for Data Science 7.1 Introduction 7.2 Convolutional Neural Network СКАЧАТЬ