○ Section 1: Machine Learning and Tabular Data
■ Chapter 1 - Introduction to Machine Learning
■ Chapter 2 - Data Tools
○ Section 2: Applied Deep Learning Architectures
■ Chapter 3 - Artificial Neural Networks
■ Chapter 4 - Convolutional Neural Networks
■ Chapter 5 - Recurrent Neural Networks
■ Chapter 6 - Attention Mechanism
■ Chapter 7 - Tree-based Neural Networks
○ Section 3: Deep Learning Design and Tools
■ Chapter 8 - Autoencoders
■ Chapter 9 - Data Generation
■ Chapter 10 - Meta-optimization
■ Chapter 11 - Multi-model arrangement
■ Chapter 12 - Deep Learning Interpretability
○ Appendix A
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