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)
Show Answer ⟶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)
Show Answer ⟶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)
Show Answer ⟶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
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