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 symbolic planning?

116

What is the difference between machine learning and artificial intelligence?

123

What is symbolic learning in AI?

105

What is non symbolic Interactionism?

What is connectionist AI?

136

What is statistical reasoning in artificial intelligence?

116

What is Bayes theorem in artificial intelligence?

117

What is reasoning and its types in artificial intelligence?

161

What is the Difference between Concept Learning and Classification Learning in Machine Learning?

224

What is the Difference between Inductive Learning and Analytical Learning in Machine Learning?

103

Explain the Algorithm of Decision Trees in Machine Learning?

Explain the Algorithm of Neural Networks (back propagation) in Machine Learning?

111

Explain the Algorithm of Probabilistic networks in Machine Learning?

Explain the Algorithm of Nearest Neighbor in Machine Learning?

146

Explain the Algorithm of Support vector machines in Machine Learning?

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Un-Answered Questions { AI Machine Learning }

Name some feature extraction techniques used for dimensionality reduction?

Do you know what's the “kernel trick” and how is it useful?

What do you understand by the f1 score?

Explain the purpose of a classifier?

What is inductive machine learning?

126

What are two techniques of Machine Learning?

127

How can you ensure that you are not overfitting with a particular model?

109

What is the difference between supervised and unsupervised machine learning?

129

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

111

How do you choose an algorithm for a classification problem?

102

What is motor sequence learning?

112

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

110

What is convex hull?

126

Is coding required for machine learning?

Explain the steps in making a decision tree.

134

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