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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What is the meaning of overfitting in machine learning?

What do you understand by machine learning?

Why overfitting occurs?

Differentiate between inductive learning and deductive learning?

When does regularization become necessary in machine learning?

What are the five popular algorithms we use in machine learning?

What are the functions of unsupervised learning?

What do you understand by decision tree in machine learning?

What is regularization? What kind of problems does regularization solve?

What do you understand by underfitting?

Why do we need to convert categorical variables into factor? Which functions are used to perform the conversion?

What are the similarities and differences between bagging and boosting in machine learning?

What do you understand by the f1 score?

What do you understand by cluster sampling?

What are the necessary steps involved in machine learning project?

Un-Answered Questions { AI Machine Learning }

Tell us why is “naive” bayes naive?

Explain the difference between a generative and discriminative model?

What are Bayesian Networks (BN) ?

What are classification problems in machine learning?

What is the difference between supervised and unsupervised learning?

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

Why do we need to convert categorical variables into factor?

What are the different methods for Sequential Supervised Learning?

Explain the Inductive Learning in Machine Learning?

What is Inductive Logic Programming in Machine Learning?

Who is associated with the theory of symbolic learning?

List out some important methods of reducing dimensionality.

What is a fourier transform?

Explain true positive, true negative, false positive, and false negative in confusion matrix with an example.

Is naive bayes a supervised or unsupervised method?

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