Advanced Concepts of Modeling in AI Class 10 MCQ

Advanced Concepts of Modeling in AI Class 10 MCQ – The CBSE has changed the syllabus of Std. X. The MCQs are made based on the new syllabus and based on the New CBSE textbook, Sample paper and Board Paper.  All the important Information are taken from the Artificial Intelligence Class X Textbook Based on CBSE Board Pattern.

Advanced Concepts of Modeling in AI Class 10 MCQ

1. Identify the model: Predicting whether a customer is eligible for a bank loan or not?
a. Classification
b. Regression
c. Both a. and b.
d. None of the above

2. Identify the model: Predicting weather for next 24 hours
a. Classification
b. Regression
c. Both a. and b.
d. None of the above

3. In which type of machine learning is the data labeled with the desired output?
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
d. Deep Learning

4. An email spam filter that learns to identify spam emails based on labeled examples is an application of:
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
d. Transfer Learning

5. A machine learning algorithm that groups similar customer purchases into clusters for recommendation systems uses:
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
d. Neural Networks

6. An AI agent playing a game and learning from its rewards and penalties is an example of:
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
d. Evolutionary Learning

7. Which of the following statements is NOT true about supervised learning?
a. Requires labeled data for training.
b. Used for classification and regression tasks.
c. Can be less efficient for large datasets.
d. Often used in image recognition applications.

8. In an unsupervised learning scenario, the goal is to:
a. Predict a specific output based on labeled data.
b. Identify patterns and relationships within unlabeled data.
c. Train an AI agent through rewards and penalties.
d. Develop complex neural network architectures.

9. Clustering algorithms are commonly used in unsupervised learning for:
a. Spam filtering
b. Image classification
c. Stock price prediction
d. Grouping similar data points

10. Reinforcement learning is particularly useful for scenarios where:
a. Large amounts of labeled data are available.
b. The desired outcome is clear, but the path to achieve it is unknown.
c. The data is structured and easily categorized.
d. The task requires reasoning and logical deduction.

11. Imagine an AI playing a game and learning to win by trial and error. This is an example of:
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
d. Natural Language Processing

12. Artificial neural networks are inspired by the structure and function of:
a. The human brain
b. Quantum computers
c. Complex mathematical models
d. High-speed processors

13. The process of adjusting the weights in a neural network to improve performance is called:
a. Activation
b. Learning
c. Optimization
d. Training

14. A neural network with multiple layers of interconnected neurons is called a:
a. Single-layer network
b. Deep Neural Network
c. Linear network
d. Perceptron

15. Neural networks are particularly well-suited for tasks involving:
a. Simple calculations and mathematical operations
b. Recognizing patterns in complex data like images and text
c. Performing logical deductions and reasoning tasks
d. Storing and retrieving large amounts of information

16. Training a neural network often requires:
a. A small set of labeled data samples
b. A significant amount of data and computational resources
c. A specific set of programming instructions
d. A human expert to guide the learning process

17. Assertion (A): Unsupervised Learning is a type of learning without any guidance.
Reasoning (R): Unsupervised learning models work on unlabeled datasets, where the data fed into the machine is random and the person training the model may not have any prior information about it.
a. Both A and R are true and R is the correct explanation for A
b. Both A and R are true and R is not the correct explanation for A
c. A is True but R is False
d. A is false but R is True

18. Assertion (A): Information processing in a neural network relies on weights and biases assigned to nodes.
Reasoning (R): These weights and biases determine how strongly a node is influenced by its inputs and its overall contribution to the next layer.
a. Both A and R are true and R is the correct explanation for A
b. Both A and R are true and R is not the correct explanation for A
c. A is True but R is False
d. A is false but R is True

19. In this learning model, the data set which is fed to the machine is labelled. Name the model. (CBSE 2022 – 2023)

20. Give 2 examples of Supervised Learning models.
a. Classification and Regression
b. Clustering and Dimensionality Reduction
c. Rule Based and Learning Based
d. Classification and Clustering

21. Statement1: There are four layers in a neural network.
Statement2:The first layer of the neural network is known as the output layer.
a. Both Statement1 and Statement2 are correct
b. Both Statement1 and Statement2 are incorrect
c. Statement1 is correct but Statement2 is incorrect
d. Statement2 is correct but Statement1 is incorrect

22. Which form of unsupervised learning does the following diagram indicate ? (CBSE 2023 – 2024)
a. Clustering
b. Regression
c. Reinforcement learning
d. Classification

23. For Data Science, usually the data is collected in the form of tables. These tabular datasets can be stored in different formats. Which of the following formats is not used for storing data in a tabular format? CBSE 2023 – 2024)
a. CSV
b. Website
c. SQL
d. Spreadsheet

24. Read the examples given below-
i. Using Chat GPT to write an email
ii. Face unlock technology of mobile phones using camera
iii. Turning off lights with IoT device
iv. Hand sanitizer dispenser having sensor
Choose the options that are not AI
a. i and ii
b. iii and i
c. iii and iv
d. i, iii and iv

25. Regression is one of the type of supervised learning model, where data is classified according to labels and data need not to be continuous, (True / False) CBSE 2022 – 2023)

26. Aditi, a student of class XII developed a chatbot that clarifies the doubts of Economics students. She trained the software with lots of data sets catering to all difficulty levels. If any student would type or ask questions related to Economics, the software would give an instant reply. Identify the domain of AI in the given scenario.
a. Computer Vision
b. Data Science
c. Natural Language Processing
d. None of these

27. Which of the following applications is not associated with Natural Language Processing (NLP)? (CBSE 2023 – 2024)
a. Sentiment Analysis
b. Speech Recognition
c. Spam Filtering in emails
d. Stock Market Analysis

28. _________helps to find the best model that represents our data and how well the chosen model will work in future. (CBSE 2022 – 2023)

29. Assertion (A): Neural networks are the backbone of deep learning algorithms
Reasoning (R): Neural networks use vast amounts of data
a. Both A and R are correct and R is the correct explanation of A
b. Both A and R are correct but R is NOT the correct explanation of A
c. A is correct but R is not correct
d. A is not correct but R is correct.

30. Assertion (A): The term used to refer to the number of pixels in an image is resolution.
Reasoning (R): Resolution in an image denotes the total number of pixels it contains, usually represented as height x width. (CBSE 2023 – 2024)
a. Both a. and R) are true and R) is the correct explanation for a..
b. Both a. and R) are true and R) is not the correct explanation for a..
c. a. is true, but R) is false.
d. a. is false, but R) is true.

31. It refers to the unsupervised learning algorithm which can cluster the unknown data according to the patterns or trends identified out of it. (CBSE 2022 – 2023)
a. Regression
b. Classification
c. Clustering
d. Dimensionality reduction

32. Infrared sensors detect infrared energy that is emitted by one’s body heat. When hands are placed in the proximity of the sensor, the infrared energy quickly fluctuates. This fluctuation triggers the pump to activate and dispense the designated amount of sanitizer. This is an example of
a. Automated machine
b. AI machine
c. Semi-automatic machine
d. Deep Learning machine

33. Google Translate is Google’s free service that instantly translates words, phrases, and web pages between English and over 100 other languages. Google translate uses —–
a. 4w problem canvas
b. Neural Networks
c. KWLH chart
d. System maps

34. Data about the houses such as square footage, number of rooms, features, whether a house has a garden or not, and the prices of these houses, i.e., the corresponding labels are fed into an AI machine. By leveraging data coming from thousands of houses, their features and prices, we can now train the model to predict a new house’s price. This is an example of
a. Reinforcement learning
b. Supervised learning
c. Unsupervised learning
d. None of the above

35. If Data is represented as “Answer”, Processing is represented as “Data” and Answer is represented as “Processing”, which of the following can be related to the description of layers in a neural network?
Choose the correct options
a. Input Layer -> Data; Output layer -> Processing; Hidden Layer -> Answer
b. Input Layer -> Processing; Output layer -> Data; Hidden Layer -> Answer
c. Input Layer -> Answer; Output layer -> Processing; Hidden Layer -> Data
d. Input Layer -> Answer; Output layer ->Data; Hidden Layer -> Processing

36. What is the role of modelling in an NLP based AI model?
a. Modelling in NLP helps in processing of AI model
b. Modelling is required to make an AI model
c. In NLP, modelling requires data pre-processing only after which the data is fed to the machine.
d. Modelling is used in simplification of data acquisition

37. Which learning approach would be most suitable for training an AI model to park the car corrrectly. (Board Paper 2025-26)
a. Supervised learning
b. Unsupervised learning
c. Transfer learning
d. Reinforcement learning

38. An e-commerce platform analyzes customer purchase patterns to recommend “Customers who bought product x also bought product y” This uses: (Board Paper 2025-26)
a. Classification model
b. Regression model
c. Association model
d. Clustering model

39. Which scenario best represents a regression problem? (Board Paper 2025-26)
a. Identifying whether an email is spam.
b. Grouping customers by behaviour.
c. Predicting tomorrow’s temperature
d. Recognizing faces in photos

40. State True/False:
Machine learning and Deep learning are part of Artificial Intelligence, but not everything that is Machine learning will be Deep learning. (Comp Board Paper 2024-25)

41, Which of the following is the second stage of an AI Project Cycle? (Comp Board Paper 2024-25)
a. Problem Scoping
b. Evaluation
c. Data Acquisition
d. Data Exploration

42. The following diagram indicates: (Comp Board Paper 2024-25)
a. Classification
b. Regression
c. Reinforcement learning
d. Clustering

43. In a neural network, what is the function of the input layer? (Comp Board Paper 2024-25)
a. It performs mathematical operations on the input data.
b. It connects neurons to the output layer for predictions.
c. It receives and passes the raw input data to the hidden layers.
d. It stores weights and biases for neural network training.

44. Which form of unsupervised learning does the following diagram indicate? (Board Paper 2023-24)
a. Clustering
b. Regression
c. Reinforcement learning
d. Classification

45. Which of the following represents an example of a recommendation system? (Board Paper 2023-24)
a. An online clothing store that offers a wide variety of clothing options.
b. A search engine that retrieves relevant web pages based on user queries.
c. An e-commerce website that displays customer reviews and ratings for products.
d. A music streaming platform that suggests songs and playlists based on user listening history.

46. Regression is one of the type of supervised learning model, where data is classified according to labels and data need not to be continuous. (True / False) (Board Paper 2022-23)

47. Which of the following is the correct feature of Neural network? (Board Paper 2022-23)
a. It can improve the efficiency of two models.
b. It is useful with small dataset.
c. They are modelled on human brains and nervous system.
d. They need human intervention.

48. In this learning model, the data set which is fed to the machine is labelled. Name the model. (Board Paper 2022-23)

49. It refers to the unsupervised learning algorithm which can cluster the unknown data according to the patterns or trends identified out of it. (Board Paper 2022-23)
a. Regression
b. Classification
c. Clustering
d. Dimensionality reduction

50. A teacher uses a rule-based program to grade students’ essays. The program was trained to look for specific keywords and phrases to assign grades. However, when students start using new words and expressions not included in the training, the program gives incorrect grades. What is the most likely reason for this issue? (Sample Paper 2025-26)
a. The rule-based program was not trained on enough essays.
b. The rule-based approach is static and cannot adapt to new words or expressions.
c. The students wrote essays that were too long.
d. The program was not tested properly.

51. Statment1: There are four layers in a neural network.
Statement2:The first layer of the neural network is known as the output layer. (Sample Paper 2024-25)
a. Both Statement1 and Statement2 are correct
b. Both Statement1 and Statement2 are incorrect
c. Statement1 is correct but Statement2 is incorrect
d. Statement2 is correct but Statement1 is incorrect

52. __ refer to the type of features that we want to collect. (Sample Paper 2024-25)

53. Srishti learnt about AI terminologies but was not able to recollect the term that is used to refer to machines that perform tasks with vast amounts of data using neural networks. Help her with the correct term. (Sample Paper 2024-25)

54. Identify the incorrect statement(s) from the following: (Sample Paper 2022-23)
(i) Deep learning is a subset of Machine Learning
(ii) Machine Learning is a subset of Deep Learning
(iii) Artificial Intelligence is a subset of Deep Learning
(iv) Deep Learning is the advanced form of AI and ML
a. only (i)
b. (ii) and (iii)
c. (i) and (ii)
d. Only (iii)

55. Divya was learning neural networks. She understood that there were three layers in a neural network. Help her identify the layer that does processing in the neural network. (Sample Paper 2022-23)
a. Output layer
b. Hidden layer
c. Input layer
d. Data layer

56. Smita is working on a project that involves over a lakh of records. Which of the following should she use to make the best project? (Sample Paper 2022-23)
a. Traditional programming
b. Manual processing
c. IoT
d. Neural networks

57. Which of the following is correct about the rule based approach? (Sample Paper 2021-22)
a. We cannot provide enough rules to the machine.
b. A drawback/feature for this approach is that the learning is static.
c. Once the rules are fed into the system, it takes into consideration any changes made in the original training dataset.
d. It can improve itself based on the feedbacks.

58. A business problem wherein we categorize whether an observation is “Safe,” “At Risk,” or “Unsafe” is an example of __. (Sample Paper 2021-22)
a. Classification
b. Clustering
c. Regression
d. Dimensionality Reduction

59. Which of the following is true about neural networks? (Sample Paper 2021-22)
a. Neural Networks tend to perform better with larger amounts of data.
b. Neural Networks tend to perform poorer with larger amounts of data.
c. Neural Networks tend to perform better with smaller amounts of data.
d. Neural Networks need no data

60. Choose the correct option (Sample Paper 2021-22)
a. Unsupervised learning ->labelled dataset, Regression
b. Supervised learning -> labelled data set, Regression
c. Unsupervised learning ->unlabelled dataset, Classification
d. Supervised learning -> unlabelled data set, Regression

61. A _______________is divided into multiple layers and each layer is further divided into several blocks called nodes. (Sample Paper 2020-21)
a. Neural Networks
b. Convolutional Neural Network (CNN)
c. Machine learning algorithm
d. Hidden Layers

62. In___________________, the machine is trained with huge amounts of data which helps it in training itself around the data. (Sample Paper 2020-21)
a. Supervised Learning
b. Deep Learning
c. Classification
d. Unsupervised Learning

63. Define Machine Learning. (Sample Paper 2020-21)
a. Machine learning is the study of computer algorithms that improve automatically through experience.
b. Refers to any technique that enables computers to mimic human intelligence.
c. Machine learning refers to computer systems (both machines and software) enables machines to perform tasks for which it is programmed.
d. Machine Learning refers to projects that allow the machine to work on a particular logic.

64. _______ refers to the AI modelling where the machine learns by itself. (Sample Paper 2020-21)
a. Learning Based
b. Rule Based
c. Machine Learning
d. Data Sciences

65. In ______, the machine is trained with huge amounts of data which helps it in training itself around the data. (Sample Paper 2020-21)
a. Machine Learning
b. Artificial Intelligence
c. NLP
d. Deep Learning

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