Table of Contents

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   Book Overview
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   Chapter 1 Introduction to AI and ML
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   Chapter 2 Essential Concepts in Artificial Intelligence and Machine Learning
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   Chapter 3 Data Understanding, Representation, and Visualization
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   Chapter 4 Linear Methods
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   Chapter 5 Perceptron and Neural Networks
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   Chapter 6 Decision Trees
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   Chapter 7 Support Vector Machines
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   Chapter 8 Probabilistic Models
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    Chapter 9 Dynamic Programming and Reinforcement Learning
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    Chapter 10 Evolutionary Algorithms
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    Chapter 11 Time Series Models
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    Chapter 12 Deep Learning
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    Chapter 13 Emerging Trends in Machine Learning
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    Chapter 14 Unsupervised Learning
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    Chapter 15 Featurization
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    Chapter 16 Designing and Tuning Model Pipelines
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    Chapter 17 Performance Measurement
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    Chapter 18 Classification
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    Chapter 19 Regression
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    Chapter 20 Ranking
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    Chapter 21 Recommendations Systems
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    Chapter 22 Azure Machine Learning
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    Chapter 23 Open Source Machine Learning Libraries
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    Chapter 24 Amazon’s Machine Learning Toolkit: Sagemaker
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    Chapter 25 Conclusion and Next Steps