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How do you handle missing or corrupted data in a dataset?
What evaluation approaches would you work to gauge the effectiveness of a machine learning model?
What are the last machine learning papers you've read?
Explain what is deep learning, and how does it contrast with other machine learning algorithms?
What is deep learning, and how does it contrast with other machine learning algorithms?
Explain the difference between bias and variance?
Define a fourier transform?
Explain how is knn different from k-means clustering?
How would you use f1 score?
How is bayes' theorem useful in a machine learning context?
Explain the difference between type I and type ii error?
Define kernel svm?
How would you use fl score?
Explain how do classification and regression differ?
Explain how do you ensure you're not overfitting with a model?
