Create Syllabus.tex

Author: DragonflyStats

Syllabus.tex

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+Lecture 1: The Learning Problem
+Lecture 2: Is Learning Feasible?
+Lecture 3: The Linear Model I
+Lecture 4: Error and Noise
+Lecture 5: Training versus Testing
+Lecture 6: Theory of Generalization
+Lecture 7: The VC Dimension
+Lecture 8: Bias-Variance Tradeoff
+Lecture 9: The Linear Model II
+Lecture 10: Neural Networks
+Lecture 11: Overfitting
+Lecture 12: Regularization
+Lecture 13: Validation
+Lecture 14: Support Vector Machines
+Lecture 15: Kernel Methods
+Lecture 16: Radial Basis Functions
+Lecture 17: Three Learning Principles
+Lecture 18: Epilogue
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