Computational Learning Theory - An Overview

Описание: Computational Learning Theory - An Overview.
We are starting with a series of lectures on Computational learning theory.
Each lecture will contain 4 parts (an introduction to the subject, key concepts, we will explain how it works and at the end we will do some practical example).
So welcome to the first video in Computational learning theory series of lectures and tutorials.
Today's topic will be an overview of Computational learning theory.
So without further ado, let's start right away.

The first part will be the introduction.
We will start with the introduction to Computational learning theory by explaining what Computational learning theory actually is, tell you few main definitions and present the chapters we are going to cover until
the end of the video.

Computational learning theory is a subset of machine learning and theoretical computer science that studies learning algorithms design and complexity.

The second part will be the key concepts.
We will mention and explain all fundamental terms and concepts which are going to be covered in their own lecture, later in Computational learning theory playlist.

For Computational learning theory, some of the key terms are:
-Probably approximately correct learning (PAC),
-Algorithmic learning theory,
-VC theory,

Then we will give a real-world example on how the concept works including illustrations and explanation.
For example, we will explain, animate and illustrate how VC theory works.

And at the end we will do some hands-on project (coding or math background) so you could get a practical meaning for the specific topic.
For example, we will explain mathematical background behind Probably approximately correct learning.

That would be all for now. See you soon with the next lecture.
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