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About Machine Learning Basic Principles
This document provides an overview of machine learning principles and methods. It discusses the components of machine learning problems, including features and labels in data, hypothesis spaces, and loss functions. It then describes several example machine learning methods, such as linear regression, logistic regression, decision trees, and neural networks. The document also covers topics like empirical risk minimization, gradient descent, model validation, overfitting, regularization, dimensionality reduction, and clustering. The goal is to introduce basic machine learning concepts from an engineering perspective.
Detailed Information
| Author: | ['Vương Vũ'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 124 |
| Language: | English |
| Format: | |
| Price: | FREE |
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