*Machine Learning 4 - [Feature Engineering, Statistical Learning Modeling, Deep Learning Modeling] — Ki B. Kim

[Feature Engineering, Statistical Learning Modeling]

· Decision Tree Learning

· Data Transformation (Logarithm, Box-Cox, Yeo-Johnson, Quantile Normalization)

[Deep Learning Modeling]

· Activation Function (Softmax, ReLU)

· Information Bottleneck Method

· Stochastic Gradient Descent (RMSProp)

· Loss Function (Cross-Entropy)

· Regularization (Dropout, L2 Regularization)

· Normalization (Batch Normalization)

*Machine Learning 3 - [Time Complexity, Deep Learning Modeling]

*Machine Learning 5 - [Cluster Analysis, Audio Signal Processing, Deep Learning Modeling]