Machine Intelligence - Lecture 9 (Cluster Validity, Probability, Fuzzy Sets, FCM)

SYDE 522 - Machine Intelligence (Winter 2019, University of Waterloo)
Target Audience: Senior Undergraduate Engineering Students
Instructor: Professor H.R.Tizhoosh (kimia.uwaterloo...)
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 9 - (Cluster Validity, Probability, Fuzzy Sets, FCM)

[@erbazkhan266]

The professor is very good at explaining stuff.

[@tarlanahad]

Unfortunately, I can't do more than liking your video. I'm really thankful to you for such an amazing (perfect, to the point and other appreciating fuzzy sets included) lecture video!

[@SamratBanerjea]

Absolute brilliance! Thank you Prof.

[@shreeshdhavle25]

Dr Hamid Thank you so much for the best explanation!

[@sajadsarlaki8090]

awesome

[@elisanealvesbackstrom4302]

Superb!