Machine Learning MCQs

This section focuses on "Machine Learning" in Data Science. These Machine Learning Multiple Choice Questions (MCQ) should be practiced to improve the Data Science skills required for various interviews (campus interview, walk-in interview, company interview), placements, entrance exams and other competitive examinations.

1. What is true about Machine Learning?

A. Machine Learning (ML) is that field of computer science
B. ML is a type of artificial intelligence that extract patterns out of raw data by using an algorithm or method.
C. The main focus of ML is to allow computer systems learn from experience without being explicitly programmed or human intervention.
D. All of the above

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2. ML is a field of AI consisting of learning algorithms that?

A. Improve their performance
B. At executing some task
C. Over time with experience
D. All of the above

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3.  p → 0q is not a?

A. hack clause
B. horn clause
C. structural clause
D. system clause

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4. The action _______ of a robot arm specify to Place block A on block B.


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5. A__________ begins by hypothesizing a sentence (the symbol S) and successively predicting lower level constituents until individual preterminal symbols are written.

A. bottow-up parser
B. top parser
C. top-down parser
D. bottom parser

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6. A model of language consists of the categories which does not include ________.

A. System Unit
B. structural units.
C. data units
D. empirical units

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7. Different learning methods does not include?

A. Introduction
B. Analogy
C. Deduction
D. Memorization

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8. The model will be trained with data in one single batch is known as ?

A. Batch learning
B. Offline learning
C. Both A and B
D. None of the above

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9. Which of the following are ML methods?

A. based on human supervision
B. supervised Learning
C. semi-reinforcement Learning
D. All of the above

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10. In Model based learning methods, an iterative process takes place on the ML models that are built based on various model parameters, called ?

A. mini-batches
B. optimizedparameters
C. hyperparameters
D. superparameters

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