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

AI Machine Learning Interview Questions

Questions Answers Views Company eMail

What is the meaning of overfitting in machine learning?

What do you understand by machine learning?

111

Why overfitting occurs?

109

Differentiate between inductive learning and deductive learning?

103

When does regularization become necessary in machine learning?

202

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

173

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?

177

Un-Answered Questions { AI Machine Learning }

Explain how would you implement a recommendation system for our company's users?

129

What are the different methods of Sequential Supervised Learning?

Explain the benefit of naive bayes mcq?

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

What are the smaller dataset techniques?

Is octave good for machine learning?

Differentiate between inductive learning and deductive learning?

103

What is symbolic machine learning?

108

Tell me how much data will you allocate for your training, validation and test sets?

171

Explain the Algorithm Technique of Supervised Learning in Machine Learning?

Tell me what is supervised versus unsupervised learning?

What is ‘tuning’ in ML?

What is ‘Overfitting’ in Machine learning?

How is decision tree pruned?

Explain the types of machine learning?

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