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How do bias and variance play out in machine learning?
What kind of problems does regularization solve?
Name some feature extraction techniques used for dimensionality reduction?
What is the main difference between a Pandas series and a single-column DataFrame in Python?
What is the “kernel trick” and how is it useful?
Tell us how do you ensure you're not overfitting with a model?
How bayes theorem is useful in a machine learning context?
What are the three stages to build the hypotheses or model in machine learning?
How do you think google is training data for self-driving cars?
Explain the two components of Bayesian logic program?
Logistic regression gives probabilities as a result then how do we use it to predict a binary outcome?
What is pca in ml?
What is keras sequential model?
What are PCA, KPCA, and ICA used for?
What is bucketing in machine learning?
