Introduction to Machine Learning Lecture 5 Fall 2016
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Machine Learning Lecture 5 Fall 2016 Comprehensive Overview
00:00:00 - Introduction 00:01:47 - Introducing Linear Models and Stochastic Gradient Descent. Lecture
Andrew G. Wilson teaches us what it means to adopt a Bayesian perspective whilst solving
Summary & Highlights for Machine Learning Lecture 5 Fall 2016
- Announcements ...
- Yeah right so um let's see where am i getting to this um i'm going to get to that in this
- Boosting.
- Decision Trees - Part 2.
- The Linear Model I - Linear classification and linear regression. Extending linear models through nonlinear transforms.
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