AI Machine Learning Interview Questions, Answers for Freshers and Experienced asked in various Company Job Interviews

AI Machine Learning Interview Questions

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Explain what is the difference between inductive machine learning and deductive machine learning?

Which do you think is more important: model accuracy or model performance?

What cross-validation technique would you use on a time series dataset?

What do you think of our current data process?

When should you use classification over regression?

What is the “kernel trick” and how is it useful?

Explain machine learning in to a layperson?

What's the f1 score? How would you use it?

What are your favorite use cases of machine learning models?

An example where ensemble techniques might be useful?

What is the difference between a generative and discriminative model?

How a roc curve works?

What is bayes' theorem? How is it useful in a machine learning context?

How would you handle an imbalanced dataset?

How do you handle missing or corrupted data in a dataset?

Un-Answered Questions { AI Machine Learning }

Define A HashTable in Machine Learning?

Why are vectors and norms used in machine learning?

What is reasoning and its types in artificial intelligence?

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What is the general principle of an ensemble method and what is bagging and boosting in ensemble method?

How do you control for biases?

What is machine learning example?

Why is “naive” bayes naive?

How Recall and True positive rate are related?

what is the function of ‘unsupervised learning’?

What are standardization and normalisation? Give one advantage of each over the other?

How would you screen for outliers and what should you do if you find one?

What is non symbolic Interactionism?

What are the classification problems in machine learning?

Why does overfitting happen?

List down various approaches to machine learning?

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