Answer / Deepika

Machine learning can be challenging to learn and master due to its mathematical and computational complexity. However, the difficulty level varies greatly depending on one's background, interest in mathematics, programming skills, and the specific area of machine learning being pursued. With dedication and practice, most people can achieve a decent understanding of machine learning.

How to decide one problem is a machine learning problem or not?

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Is it better to have too many false positives or too many false negatives? Explain.

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Is python the best language for machine learning?

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What is data pre-processing technique for machine learning?

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Tell us do you have research experience in machine learning?

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What's the f1 score? How would you use it?

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How do deductive and inductive machine learning differ?

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Explain the Algorithm of Decision Trees in Machine Learning?

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Explain the difference between bayesian and frequentist?

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Explain the difference between bayes and naive bayes?

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What are the smaller dataset techniques?

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Can naive bayes be used for multiclass classification?

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