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What kind of problems does regularization solve?
What is a classifier in machine learning?
Is it better to have too many false positives or too many false negatives? Explain.
What is bayes' theorem? How is it useful in a machine learning context?
How do you ensure you're not overfitting with a model?
List down various approaches to machine learning?
Can you explain bias-variance trade-off?
What are the last machine learning papers you've read?
What is the difference between artificial intelligence and machine learning?
Why is naïve bayes machine learning algorithm naïve?
What is 'naive' in the Naive Bayes classifier?
What are the three stages of building the hypotheses or model in machine learning?
Explain Principal Component Analysis (PCA)?
Explain the Algorithm of Neural Networks (back propagation) in Machine Learning?
Explain the machine learning techniques?
