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Statistical Foundations of Actuarial Learning and its Applications

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Cover of 'Statistical Foundations of Actuarial Learning and its Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Exponential Dispersion Family
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    Chapter 3 Estimation Theory
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    Chapter 4 Predictive Modeling and Forecast Evaluation
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    Chapter 5 Generalized Linear Models
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    Chapter 6 Bayesian Methods, Regularization and Expectation-Maximization
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    Chapter 7 Deep Learning
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    Chapter 8 Recurrent Neural Networks
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    Chapter 9 Convolutional Neural Networks
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    Chapter 10 Natural Language Processing
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    Chapter 11 Selected Topics in Deep Learning
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    Chapter 12 Appendix A: Technical Results on Networks
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    Chapter 13 Appendix B: Data and Examples
Attention for Chapter 3: Estimation Theory
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