Machine Intelligence - Lecture 10 (Regression, Neurons, Perceptron, Learning)

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SYDE 522 – Machine Intelligence (Winter 2019, University of Waterloo)

Target Audience: Senior Undergraduate Engineering Students

Course Outline - The objective of this course is to introduce the students to the main concepts of machine intelligence as parts of a broader framework of “artificial intelligence”. An overview of different learning, inference and optimization schemes will be provided, including Principal Component Analysis, Support Vector Machines, Self-Organizing Maps, Decision Trees, Backpropagation Networks, Autoencoders, Convolutional Networks, Fuzzy Inferencing, Bayesian Inferencing, Evolutionary algorithms, and Ant Colonies.

Lecture 10 - (Regression, Neurons, Perceptron, Learning)

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E(w0, w1| x) = 1/2 SUM .... etc >> Why you put 1/2 and square in the end of equeation? at 13th minutes
Thank you

mohammedsinwi

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