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About Concise Machine Learning PDF
This document contains lecture notes for an introductory machine learning course. The course covers classification, regression, clustering, and dimensionality reduction methods. It focuses on a small selection of popular and useful algorithms that can be covered in a single semester, including perceptrons, support vector machines, Gaussian discriminant analysis, decision trees, neural networks, principal components analysis, and spectral clustering. The notes are intended to be concise as they were compiled from actual classroom lectures without slides. Additional details and readings are provided on the course website.
Detailed Information
| Author: | ['keyyongpark'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 172 |
| Language: | English |
| Format: | |
| Price: | FREE |
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