Answer / Pavnesh Kumar

Python's popularity in machine learning stems from its simplicity and the ease with which one can prototype, experiment, and implement complex algorithms. Additionally, the availability of powerful libraries like TensorFlow, PyTorch, and Scikit-learn makes Python a preferred choice for many researchers and practitioners.

Do you think that treating a categorical variable as a continuous variable would result in a better predictive model?

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Why do we need to convert categorical variables into factor?

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What is dimension reduction in Machine Learning?

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Which one would you prefer to choose – model accuracy or model performance?

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What does linear in ‘linear regression’ actually mean?

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What is the Model Building in Machine Learning?

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How do we separate one dimensional, two dimensional and three-dimensional data?

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An example where ensemble techniques might be useful?

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Explain how do classification and regression differ?

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What are the three stages of building the hypotheses or model in machine learning?

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What is the difference between bayesian and frequentist?

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What is sequential data in machine learning?

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