Topics TODO

[JC-ProgJava]

Evaluation

• Confusion matrices
  • Source 2
• Precision and recall

Regression / Loss/Cost Function

• Polynomial Regression (put into Chapter 5)
• Ridge & LASSO Regression
• Elastic Net Regression
• Logistic (Probabilistic) Regression

Regularization Techniques

• Early Stopping
• Dropout
• Weight Decay (L2 Regularization)

Other Architectures (Appendix and New Chapters)

• Neural Networks
  • Recurrent Neural Networks (RNN)
  • Auto-encoders
  • Generative Adversarial Networks (GAN)
• Support Vector Machines (SVM)
• Decision Trees
• Reinforcement Learning
  • Q-Learning
• Unsupervised Learning
  • K-Means
  • K-Nearest Neighbor
• Ensemble Learning
  • Random Forests

Preprocessing

• Dimensionality Reduction

[JC-ProgJava]

• Update 'A Readable Bibliography'
• Further Reading