Artificial Intelligence-10th Questions
Browse 294 Artificial Intelligence questions with expert-verified, step-by-step solutions — NCERT, exemplar and previous-year questions, organised by chapter.
- Q81 CBSE Board 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.
- Q82 CBSE Board 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.
- Q83 CBSE Board 2026Statement 1 : Overfitting occurs when a model memorizes the training data rather than learning patterns. Statement 2 : Using the same data for training and evaluation helps the model give accurate results.
- (a)Both statements are correct.
- (b)Both statements are incorrect.
- (c)Statement 1 is correct but statement 2 is incorrect.
- (d)Statement 1 is incorrect but statement 2 is correct.
- Q84 CBSE Board 2026A spam e-mail detection system correctly identifies an e-mail as “Not Spam” when it actually is not spam. This represents :
- (a)True Positive (TP)
- (b)True Negative (TN)
- (c)False Positive (FP)
- (d)False Negative (FN)
- Q85 CBSE Board 2026In the context of autonomous vehicle safety systems, which type of error would be most critical to minimize ?
- (a)False Positive (detecting danger when there isn’t any)
- (b)False Negative (failing to detect actual danger)
- (c)True Positive (detecting danger correctly)
- (d)True Negative (correctly identifying that there is no danger)
- Q86 CBSE Board 2026Which of the following best describes overfitting in the context of train-test split ?
- (a)The model performs well on both training and test data.
- (b)The model performs well on training data but poorly on test data.
- (c)The model performs poorly on both training and test data.
- (d)The model performs poorly on training data but well on test data.
- Q87 CBSE Board 2026In supervised learning, what is the purpose of the testing dataset ?
- (a)To train the model.
- (b)To evaluate the model’s accuracy.
- (c)To create new features.
- (d)To label the data.
- Q88 CBSE Board 2026In a fire alarm system, if the model predicts “Fire Present” when there is actually no fire, this is classified as :
- (a)True Positive (TP)
- (b)True Negative (TN)
- (c)False Positive (FP)
- (d)False Negative (FN)
- Q89 CBSE Board 2026Recall is a classification metrics that measures :
- (a)How many False positives are correctly identified by the model.
- (b)How many actual positive cases were correctly identified by the model.
- (c)How many negative cases were correctly identified by the model.
- (d)The overall accuracy of the model.
- Q90 CBSE Board 2026Precision is defined as :
- (a)The ratio of correctly predicted positive observations to total observations.
- (b)The ratio of correctly predicted positive observations to total predicted positive observations.
- (c)The ratio of correctly predicted negative observations to total observations.
- (d)The harmonic mean of true positives and true negatives.
- Q91 CBSE Board 2026What is the primary purpose of train-test split in model evaluation ?
- (a)To increase the size of the dataset.
- (b)To reduce computational complexity.
- (c)To estimate the performance of the machine learning model on new data.
- (d)To improve the accuracy of the training process.
- Q92 CBSE Board 2026In machine learning, the error is used to see how accurately the model can predict data.
- Q93 CBSE Board 2026This ethical concern refers to an honest explanation how the chosen evaluation metrics work and produce results without keeping any information hidden. Name this ethical concern that should be kept in mind while evaluating an AI model.
- (a)Bias
- (b)Transparency
- (c)Accountability
- (d)Accuracy
- Q94 CBSE Board 2026An AI model was tested with 1000 test samples. If True Positive (TP) = 200, True Negative (TN) = 600, False Positive (FP) = 100, False Negative (FN) = 100, how many total predictions were correct ?
- (a)300
- (b)600
- (c)800
- (d)900
- Q95 CBSE Board 2026Which of the following best describes model evaluation in artificial intelligence ?
- (a)The process of creating new datasets for training
- (b)The process of using different evaluation metrics to understand a machine learning model’s performance
- (c)The process of selecting algorithms for model building
- (d)The process of data preprocessing and cleaning
- Q96 CBSE Board 2026Explain Train-test split technique with respect to machine learning algorithm.
- Q97 CBSE Board 2026Define Accuracy. Also give one example to explain why high accuracy does not always mean a model is performing well in real-world situations.
- Q98 CBSE Board 2026Read the following paragraph and answer the questions that follow : PQR Security Solutions has designed an AI Model to detect cyber attacks on E-Commerce websites. For this, various network activities were monitored and analyzed on one of the websites. The model was tested on a dataset of 1500 network activities. Out of these, the model correctly predicted that 1000 were cyber attacks. It also correctly identified that 250 were not cyber attacks. However, the model predicted that 200 were cyber attacks but actually they were not. Additionally, it predicted that 50 were not cyber attacks but they actually were.
- Q99 CBSE Board 2026An AI model has been developed to predict whether electric vehicle batteries need replacement based on performance data. The model was tested on a dataset of 700 vehicles and the resulting confusion matrix is as follows : The above Confusion Matrix can also be represented as follows :
- Q100 CBSE Board 2025_________ is defined as the percentage of correct predictions out of all the observations.
- (a)Precision
- (b)Accuracy
- (c)Recall
- (d)F1