Exploring Machine Learning 10 701 Fall 2013 Lecture 17
Let's dive into the details surrounding Machine Learning 10 701 Fall 2013 Lecture 17.
- Cornell class CS4780. (Online version: https://tinyurl.com/eCornellML )
- Topics: principal component analysis (PCA), deep
- Topics: course logistics, high-level overview of
- graphical models: factor graphs, Markov random fields, junction trees Note: interesting part starts at minute 4:30 due to slight ...
- Topics: Practice working with probability distributions involving linear algebra and matrix calculus
In-Depth Information on Machine Learning 10 701 Fall 2013 Lecture 17
The bootstrap. Directed Graphical Models Bayes Ball Algorithm Introduction to Topics: hidden Markov model (HMM), belief propagation, junction tree algorithm Lecture
Lecture
That wraps up our extensive overview of Machine Learning 10 701 Fall 2013 Lecture 17.
