Class 10 Artificial Intelligence
Advanced Concepts of Modeling in AI
37 Class 10 Artificial Intelligence questions on Advanced Concepts of Modeling in AI from the CBSE board papers 2023–2026, each with its answer and a step-by-step solution.
Questions · page 2 of 2
- Q21 CBSE 2025In a neural network, what is the function of the input layer ?
- (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.
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(c) It receives and passes the raw input data to the hidden layers. - Q22 CBSE 2025Explain the following with respect to Unsupervised Learning Models :
- (a)Clustering
- (b)Dimensionality Reduction
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Clustering groups unlabelled data by the patterns found in it; dimensionality reduction reduces the dimensions of data while keeping it meaningful.
(a) Clustering is an unsupervised learning algorithm that clusters unknown, unlabelled data according to the patterns or trends identified out of it; the patterns may or may not be known to the developer. (b) Dimensionality Reduction reduces the number of dimensions of the data: as dimensions are dropped the information starts getting distorted, so it reduces them while still keeping the data meaningful. - Q23 CBSE 2025Consider the following diagram. It explains how a system of organized machine learning algorithms perform certain tasks. Identify the concept and explain its working.Step-by-step solution →
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The concept is a Neural Network: the input layer acquires data, hidden layers process it, and the output layer gives the final answer.
The concept is a Neural Network, a system of organising machine learning algorithms to perform a task, modelled on how neurons in the human brain behave. It works in three kinds of layer. The input layer acquires the data and feeds it in, doing no processing. Each node of the hidden layers runs its own machine learning algorithm and passes its result to the next layer. The output layer gives the final answer to the user. - Q24 CBSE 2024Which of the following represent a machine that is smart but not considered Artificial Intelligence (AI) enabled ?
- (a)A robotic vacuum cleaner that can navigate and clean floors autonomously.
- (b)A chatbot that engages in natural language conversations and answers questions.
- (c)A smartphone with facial recognition for unlocking the device.
- (d)A digital alarm clock that rings at a set time every morning.
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(d) A digital alarm clock that rings at a set time every morning. - Q25 CBSE 2024Which form of unsupervised learning does the following diagram indicate ?
- (a)Clustering
- (b)Regression
- (c)Reinforcement learning
- (d)Classification
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(a) Clustering - Q26 CBSE 2024When a machine possesses the ability to mimic human traits, i.e., make decisions, predict the future, learn, and improve on its own, it is said to have :
- (a)Computational Skills
- (b)Learning Capability
- (c)Artificial Intelligence
- (d)Cognitive Processing
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(c) Artificial Intelligence - Q27 CBSE 2024Differentiate between Machine Learning (ML) and Deep Learning (DL).Step-by-step solution →
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ML improves with experience from the data fed to it, while DL, a subset of ML, trains itself on vast data.
Machine Learning: the machine improves with experience, learning from data fed to it. Deep Learning: a subset of ML that trains itself on vast data using multiple ML algorithms. - Q28 CBSE 2024For a healthcare organisation’s objective of predicting disease outbreaks and efficiently allocating resources through the analysis of medical records, would you recommend using supervised learning or unsupervised learning as the preferred machine learning approach ? Explain your choice briefly.Step-by-step solution →
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Supervised learning, because past records with known outcomes train a model to predict outbreaks and guide resource allocation.
Supervised learning. Past medical records carry known outcomes (whether an outbreak occurred), so a model trained on this labelled data can predict future outbreaks and guide resource allocation. - Q29 CBSE 2024What are Neural networks ? Briefly explain all the layers of a neural network.Step-by-step solution →
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A neural network is a layered system of machine learning algorithms, modelled on brain neurons, made of input, hidden and output layers.
Neural networks are modelled on how neurons in the human brain behave: a system of machine learning algorithms, organised in layers, that extracts features from data automatically. The input layer acquires the data and feeds it in without processing. The hidden layers do all the processing; each node runs its own ML algorithm and passes its output on. The output layer gives the final result to the user, without processing. - Q30 CBSE 2024Consider the following graphs (Figure 1 and Figure 2) that demonstrate the two types of Supervised Learning Models of Artificial Intelligence. Identify and explain each model giving suitable examples of each.Step-by-step solution →
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Figure 1 is Classification (labels, e.g. spam or not spam); Figure 2 is Regression (predicts numbers, e.g. a house price).
Figure 1 is a Classification model: it works on labelled, discrete data, and the dashed line separates the two classes, so a new item gets a class label, for example spam or not spam, or students' grades. Figure 2 is a Regression model: a curve is fitted through continuous data to predict a numerical value, for example next year's salary or a house price. - Q31 CBSE 2023Regression 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)Step-by-step solution →
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False - Q32 CBSE 2023Which of the following is the correct feature of Neural network ?
- (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.
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(c) They are modelled on human brains and nervous system. - Q33 CBSE 2023In this learning model, the data set which is fed to the machine is labelled. Name the model.Step-by-step solution →
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The model is supervised learning, because it is fed labelled data.
Supervised learning. The data set fed to the machine is labelled, so every example carries its correct answer and the machine learns by comparing its own prediction with that answer. Its two kinds are classification and regression. - Q34 CBSE 2023It refers to the unsupervised learning algorithm which can cluster the unknown data according to the patterns or trends identified out of it.
- (a)Regression
- (b)Classification
- (c)Clustering
- (d)Dimensionality reduction
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(c) Clustering - Q35 CBSE 2023What is Dimensionality Reduction ?Step-by-step solution →
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It is an unsupervised model that reduces the number of features describing the data while keeping it meaningful.
Dimensionality reduction is an unsupervised learning model that reduces the number of dimensions, that is the features describing each record, while still keeping the data meaningful - because information starts getting distorted as dimensions are dropped. - Q36 CBSE 2023Ms. Sooji is a beginner in the field of Artificial Intelligence. She got confused among the core terms like Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL). Many a times, these terms are used interchangeably but are they the same ? Justify your answer. Help her in understanding these terms by drawing a well labelled diagram to depict the interconnection of these three fields.Step-by-step solution →
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No: ML is a subset of AI that learns from data, and DL is a subset of ML using many-layered neural networks.
No. Artificial Intelligence is making a machine mimic human intelligence; Machine Learning is a subset of AI in which the machine learns the rules from data; Deep Learning is a subset of ML that learns through many-layered neural networks and finds the features itself. Every DL model is ML and every ML model is AI, but not the reverse - a rule-based expert system is AI without being ML. The diagram is three nested circles labelled AI, ML and DL from outside in. - Q37 CBSE 2023Will it be valid to say that not all the devices which are termed as “smart” are AI-enabled ? Justify this statement. Explain any two examples from the daily life which are commonly misunderstood as AI.Step-by-step solution →
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Yes, not all smart devices are AI-enabled: fixed-rule automation, like a washing machine or an automatic door, does not learn from data.
Yes, it is valid. Smart usually means connected, programmable or automatic, and says nothing about AI. A device is AI-enabled only if it learns from data and improves; one that follows fixed rules written by a person is automation. Two examples: an automatic washing machine runs a cycle an engineer programmed and never notices how dirty the clothes are; an automatic door opens on its sensor and has learnt nothing after a thousand openings.