Introduction to Machine Learning

Introduction to Machine Learning CAP 4630 Xingquan (Hill) Zhu

Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Face Detection Demo ,[object Object],[object Object],[object Object],[object Object]

More Complicated Examples ,[object Object],[object Object],Machine Learning Yes or No! How much confidence? Fst: Yes, 90% Snd: No, 70% Thd: No, 90% Fth: No, 80%

ALVINN drives 70mph on highways CMU

More Complicated Example Regression ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],y = wx + w 0 http://www.theparticle.com/applets/ml/index.html

Outline ,[object Object],[object Object],[object Object],[object Object]

What is Machine Learning? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

What is Machine Learning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

“ Learning” … ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Machine Learning: Creating a Classifier Adaptively ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Machine Learning Output ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

What is Pattern Recognition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Typical Decision Process ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Example: Feature Selection ,[object Object],[object Object],[object Object]

Example: Feature Selection ,[object Object],[object Object]

Example: Multiple Features ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Example: Multiple Features Feature vector - A vector of observations (measurements). - is a point in feature space . Hidden state - Cannot be directly measured. - Patterns with equal hidden state belong to the same class. Task - To design a classifer (decision rule) which decides about a hidden state based on an onbservation. Pattern

Overfitting and underfitting underfitting overfitting good fit

Example: Cost of Error ,[object Object],[object Object],[object Object],[object Object]

The actual forms of the decision model (Patterns) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Resources: Datasets ,[object Object],[object Object],[object Object],[object Object]

Resources: Journals ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Resources: Conferences ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Introduction to Machine Learning

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Introduction to Machine Learning