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 }

What are some common unsupervised tasks other than clustering?

Why overfitting occurs?

Tell us where do you usually source datasets?

What is the difference between symbolic and non symbolic AI?

Explain the objective of machine learning?

What do you mean by parametric models?

What is difference between supervised and unsupervised learning algorithms?

How is KNN different from K-means clustering?

Is Python necessary for machine learning?

What is sequence learning?

How can we use your machine learning skills to generate revenue?

What according to you, is the standard approach to supervised learning?

Why is python best for machine learning?

What is dimensionality reduction? Explain in detail.

List down various approaches to machine learning?

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