Machine Learning Safety

Table of Contents

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   Book Overview
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   Chapter 1 Machine Learning Basics
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   Chapter 2 Model Evaluation Methods
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   Chapter 3 Safety and Security Properties
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   Chapter 4 Practice
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   Chapter 5 Decision Tree
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   Chapter 6 K-Nearest Neighbor
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   Chapter 7 Linear Regression
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   Chapter 8 Naive Bayes
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    Chapter 9 Loss Function and Gradient Descent
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    Chapter 10 Deep Learning
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    Chapter 11 Verification of Deep Learning
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    Chapter 12 Enhancement to Safety and Security of Deep Learning
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    Chapter 13 Deep Reinforcement Learning
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    Chapter 14 Testing Techniques
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    Chapter 15 Reliability Assessment
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    Chapter 16 Assurance of Machine Learning Lifecycle
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    Chapter 17 Probabilistic Graph Models for Feature Robustness