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About Machine Learning - A First Course For Engineers and Scientists
This document provides an overview of a textbook on machine learning for engineers and scientists. The textbook covers fundamental machine learning concepts including supervised learning algorithms like k-nearest neighbors and decision trees. It also discusses parametric models, evaluating model performance, learning parametric models, neural networks, ensemble methods, kernels, Bayesian approaches, and generative models. The goal of the textbook is to introduce machine learning techniques that engineers and scientists can apply to their work.
Detailed Information
| Author: | ['Usman Ahmed'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 348 |
| Language: | English |
| Format: | |
| Price: | FREE |
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