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Class 10 Computer Science Chapter 6 MCQs PDF Free Download | ML Types | New Syllabus 2026

Class 10 Computer Science Chapter 6 MCQs PDF is a useful study resource for students preparing for Computer Science and Entrepreneurship according to the New Syllabus 2026 for Punjab Boards. This chapter focuses on important concepts related to Machine Learning (ML) Types and provides students with important multiple-choice questions for exam preparation. In this post, students can practice complete solved MCQs and download the free PDF for offline study and revision. These Chapter 6 MCQs are helpful for Class 10 Punjab Board students preparing for school tests, online MCQ practice, and annual Computer Science examinations.

10CSE Chapter 6 6.2 Machine Learning Types

6.2 Machine Learning Types

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If the system is grouping without given answers, it is:

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Which of the following provide high accuracy?

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Unsupervised learning is when the machine:

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In supervised learning, the machine is given data with:

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Think of Supervised Learning as learning with a teacher, and Unsupervised Learning as:

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Who Compare its own results with correct results?

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When grouped or unlabeled data is arrived, we used?

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Which of the following is an example of supervised learning? (Analytical / Conceptual)

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Which of the following help to market product in better way?

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Supervised Learning uses labeled data to:

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Give data without any label?

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Supervised learning is when the machine is trained using:

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Unsupervised Learning uses unlabeled data to:

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How many types of machine learning?

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In unsupervised learning, the machine is given:

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Which of the following is an example of unsupervised learning in school? (Analytical / Conceptual)

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Computer Science and Entrepreneurship 10th Class New Syllabus 2026 MCQs with Answers

 
Chapter 6 Introduction to AI and Machine Learning
[Tech ICT Group (Chapter 5) and Simple Computer Science Group]

6.1 Overview of AI and ML

6.2 Machine Learning Types

6.3 Practical Applications of AI and ML

6.4 Supervised and Unsupervised Algorithm

6.5 Evaluating Model Performance

Complete Exercise Solution

Complete Chapter MCQs

 

 
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