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About 2 Machine Learning Overview v3.5
The document provides an overview of machine learning concepts and algorithms. It discusses: 1) The objectives of the course are to understand learning algorithm definitions, the machine learning process, related concepts like hyperparameters and cross-validation, and common machine learning algorithms. 2) Machine learning algorithms are trained on sample data to learn patterns and make predictions on new data. Supervised learning uses labeled data, unsupervised learning uses unlabeled data, and reinforcement learning learns from rewards/punishments. 3) Classification, regression, and clustering are common problem types addressed by machine learning algorithms. Classification predicts discrete classes, regression predicts continuous values, and clustering groups unlabeled data.
Detailed Information
| Author: | ['Dany Sanchez'] |
|---|---|
| Publication Year: | 2024 |
| Pages: | 95 |
| Language: | English |
| Format: | |
| Price: | FREE |
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