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 most frequent metric to assess model accuracy for classification problems?

136

How do we know which machine learning algorithm is better for us to solve our problem?

170

How will you choose the most appropriate machine learning algorithm for your classification problem?

When should one use mean absolute error over root mean square error as a performance measure for regression problems?

154

What does linear in ‘linear regression’ actually mean?

168

What is the “curse of dimensionality?

What do you understand by decision tree classification?

What do you mean by parametric models?

How do we separate one dimensional, two dimensional and three-dimensional data?

103

How will you explain machine learning into a layperson?

What do you mean by parametric models? Also, give some examples of them?

Why do we convert categorical variables into factor?

What type of learning is needed when the system needs to adapt to rapidly changing data?

120

How to decide one problem is a machine learning problem or not?

187

What is the sigmoid function in machine learning?

110

Un-Answered Questions { AI Machine Learning }

What is batch statistical learning?

141

Tell us an example where ensemble techniques might be useful?

What is an Incremental Learning algorithm in ensemble?

What are some methods of reducing dimensionality?

How will you explain a linked list and an array?

Does 100% precision mean that our model predicts all the values correctly?

Which os is good for machine learning?

115

What is regression in machine learning with example?

What is the box-cox transformation used for?

Why instance-based learning algorithm sometimes referred to as lazy learning algorithm?

Explain the Algorithm Technique of Transduction in Machine Learning?

Tell me what is supervised versus unsupervised learning?

Why is “naive” bayes naive?

What is ‘tuning’ in ML?

What’s the trade-off between bias and variance?

103

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