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About Artificial Inteligence PDF
The document provides an overview of machine learning concepts including supervised and unsupervised learning. Supervised learning involves providing input-output pairs to train a model to make predictions on new data, while unsupervised learning allows the computer to learn from unlabeled data. Features are important for building robust models, with more relevant features needed to classify complex problems. The training process provides a set of inputs and expected outputs to create a model or hypothesis that can then map new data to the trained categories. Various algorithms can be used depending on the problem and available data. The basic recipe is to first check model performance on training data and make the model more complex if needed.
Detailed Information
| Author: | ['LPomelo7'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 328 |
| Language: | English |
| Format: | |
| Price: | FREE |
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