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Few Topics are:

• supervised learning
• MLE
• nonlinear least squares,
• bootstrapping
•  Fisher information
•  model selection and evaluation
•  shrinkage/regularization \
•  ridge regression
•  LASSO
•  stepwise regression
•  ideal Bayes classifier and predictor
• Neural networks
• Visualizing black-box predictive models
• Classification and regression trees
• Nearest neighbors
• Local methods and kernel smoothing
• Generalized additive models
•  projection pursuit regression
• Ensemble methods
•  Bagging
•  stacking
•  boosted trees
•  random forests
• Support vector machines
• Naive Bayes
• Unsupervised learning
• predictive modeling
•  PCA
•  nonlinear dimensionality reduction
•  kernel density estimation