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Machine Learning Techniques Probabilistic Models
Time:0:00


Acknowledgments
Time:4:46


Outline
Time:5:10


Predict a second heart attack
Time:8:27


Stock price prediction
Time:8:60


Handwritten Text
Time:9:44


Cancer classification
Time:10:13


Netflix
Time:10:31


Spam Filters
Time:11:07


Financial crisis prediction
Time:12:43


Stock market prediction
Time:13:35


Cash management in ATM networks
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What is Machine Learning?
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Example
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What is Machine Learning?
Time:25:15


Example
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Error or Loss function
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Training vs. Testing
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Training vs. Testing
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Questions
Time:31:50


Data
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Data
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Statistical ML approach
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Introduction to Probability
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Random variables
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Discrete random variables
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Continuous random variable
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Joint probability Pr(x,y)
Time:43:27


Joint probability
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Marginalization (Sum Rule)
Time:48:37


Marginalization
Time:51:25


Marginalization (Sum Rule)
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Marginalization
Time:52:23


Conditional probability
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Product rule
Time:59:39


Factorization
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Factorization
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Bayes' rule
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Bayes' rule
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Bayes' rule
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Recap
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Sum Rule Product Rule Recap
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Independence
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Expectation
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Thank You
Time:1:27:12