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            課程目錄:Data Mining & Machine Learning with R培訓
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            Introduction to Data mining and Machine Learning
            Statistical learning vs. Machine learning
            Iteration and evaluation
            Bias-Variance trade-off
            Regression
            Linear regression
            Generalizations and Nonlinearity
            Exercises
            Classification
            Bayesian refresher
            Naive Bayes
            Dicriminant analysis
            Logistic regression
            K-Nearest neighbors
            Support Vector Machines
            Neural networks
            Decision trees
            Exercises
            Cross-validation and Resampling
            Cross-validation approaches
            Bootstrap
            Exercises
            Unsupervised Learning
            K-means clustering
            Examples
            Challenges of unsupervised learning and beyond K-means
            Advanced topics
            Ensemble models
            Mixed models
            Boosting
            Examples
            Multidimensional reduction
            Factor Analysis
            Principal Component Analysis
            Examples

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