Answer / Saurabh Sonkar

The primary purpose of machine learning is to enable computers to learn from data, without being explicitly programmed. This allows machines to make decisions, predictions, and solve problems based on patterns in the data they've been trained on. Common applications include image recognition, speech recognition, fraud detection, recommendation systems, and predictive analytics.

Name some feature extraction techniques used for dimensionality reduction?

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What do you understand by Eigenvectors and Eigenvalues?

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How would you evaluate a logistic regression model?

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Explain what are some methods of reducing dimensionality?

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Explain the benefit of naive bayes mcq?

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What do you understand by decision tree classification?

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