In this lecture we look at linear classification, i.e. the problem of fitting a straight line to classify two different sets of points.
These videos are recordings of lectures from the module Introduction to AI run by The School of Computer Science at the University of Birmingham, UK.
More information at: cs.bham.ac.uk/internal/courses/intro-ai
In this lecture we look at the problem of fitting a straight line to some training data in order to use it to make predictions.
In this lecture we look at information gain (entropy reduction) as a mechanism for selecting an attribute test when learning a decision tree from data.
In this lecture we look at the decision tree representation and the ID3 algorithm for learning decision trees from data.
In this lecture we take a high-level look at the agent-based approach to AI plus reinforcement learning, unsupervised learning and supervised learning.
Content from the Intro to AI module run by Nick Hawes in the School of Computer Science at the University of Birmingham.
More stuff from “Intro to AI 2011”
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