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Introduction to Transfer Learning

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Cover of 'Introduction to Transfer Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 From Machine Learning to Transfer Learning
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    Chapter 3 Overview of Transfer Learning Algorithms
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    Chapter 4 Instance Weighting Methods
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    Chapter 5 Statistical Feature Transformation Methods
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    Chapter 6 Geometrical Feature Transformation Methods
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    Chapter 7 Theory, Evaluation, and Model Selection
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    Chapter 8 Pre-Training and Fine-Tuning
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    Chapter 9 Deep Transfer Learning
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    Chapter 10 Adversarial Transfer Learning
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    Chapter 11 Generalization in Transfer Learning
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    Chapter 12 Safe and Robust Transfer Learning
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    Chapter 13 Transfer Learning in Complex Environments
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    Chapter 14 Low-Resource Learning
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    Chapter 15 Transfer Learning for Computer Vision
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    Chapter 16 Transfer Learning for Natural Language Processing
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    Chapter 17 Transfer Learning for Speech Recognition
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    Chapter 18 Transfer Learning for Activity Recognition
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    Chapter 19 Federated Learning for Personalized Healthcare
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    Chapter 20 Concluding Remarks
Attention for Chapter 4: Instance Weighting Methods
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