Answer / Khushboo Srivastava

A typical machine learning project involves several steps: problem understanding, data collection and preprocessing, feature engineering, model selection and training, evaluation, tuning, and deployment. These steps may be iterated multiple times to improve performance.

What do you understand by decision tree in machine learning?

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Explain me what's the trade-off between bias and variance?

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Explain what are some methods of reducing dimensionality?

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What is 'naive' in the Naive Bayes classifier?

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Which is best language for machine learning?

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What is the difference between artificial learning and machine learning?

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Explain the difference between bayesian and frequentist?

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What is bias-variance decomposition of classification error in ensemble method?

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What is accuracy score in machine learning?

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“People who bought this, also bought….” Recommendations on amazon are a result of which machine learning algorithm?

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Explain the most common types of machine learning task?

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