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Machine Learning for Practical Decision Making

Overview of attention for book
Cover of 'Machine Learning for Practical Decision Making'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Machine Learning
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    Chapter 2 Statistics
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    Chapter 3 Overview of Machine Learning Algorithms
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    Chapter 4 Data Preprocessing
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    Chapter 5 Data Visualization
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    Chapter 6 Linear Regression
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    Chapter 7 Logistic Regression
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    Chapter 8 Decision Trees
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    Chapter 9 Naïve Bayes
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    Chapter 10 K-Nearest Neighbors
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    Chapter 11 Neural Networks
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    Chapter 12 K -Means
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    Chapter 13 Support Vector Machine
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    Chapter 14 Voting and Bagging
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    Chapter 15 Boosting and Stacking
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    Chapter 16 Future Directions and Ethical Considerations
Attention for Chapter 14: Voting and Bagging
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