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Body of Knowledge
Advanced Data Science

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Advanced Data Science

Approaches
Prediction
Learning
Inference
Least squares regression
Probabilistic regression
Maximum likelihood
Regularization and features selection
Bayesian
Mixed approach
Binary classification
Probabilistic classification
Credit default classification
Background
Fit and assessment
Logistic regression
Interactions
Encoding
Regularization
Trees
Gradient boosting
Cross-validation
Least squares autoencoders
Graphical models
k-means clustering
Shrinkage
Overview
Least squares dynamic models
Wiener-Kolmogorov filtering
Dynamic principal component
Probabilistic state space models
Background
Shrinkage
Bias reduction
Functional bias reduction
Linear basis expansion
Quasi-linear adaptive basis
Adaptive networks
Gradient boosting
Kernel trick
Generalized probabilistic inference
Minimum relative entropy
Analytical implementation
Flexible probabilities implementation
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