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Machine Learning (The Linear Model (Pictorial Differencefrom…
Machine
Learning
Introduction
Traditional vs
Learning Approach
purely experimental
Learning Flowchart
The Linear Model
Pictorial Difference
from Classification
Explicit Formula
Linear Model
as a Basis
Learning Theory
Generalizing
Hoeffding Inequality
Improving the
Union Bound
Reduce to Polynominal
Reduce to Finite
Growth Function/
VC Dimension
How to Calculate
Interpretation
Generalization Bound
Complex model=
low E_in, high \( \Omega. \)
Bias Variance
Tradeoff
Neural Networks
Gates with Perceptons
Transition to
Neural Network
Back propagation
Algorithm
Logistic Regression
Likelihood as
Error Measure
How it transform s