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Tell us how do deductive and inductive machine learning differ?
Tell us how is a decision tree pruned?
Tell us which do you think is more important: model accuracy or model performance?
What is the f1 score? How would you use it?
What is the difference between type I and type ii error?
What's the “kernel trick” and how is it useful?
How do you think google is training data for self-driving cars?
Name some feature extraction techniques used for dimensionality reduction?
What are some differences between a linked list and an array?
How can we use your machine learning skills to generate revenue?
How do you ensure you're not overfitting with a model?
What is a fourier transform?
Why is “naive” bayes naive?
How do deductive and inductive machine learning differ?
What is your training in machine learning and what types of hands-on experience do you have?
