Students find these Class 10 AI MCQ Chapter 2 AI Project Cycle Class 10 MCQ Online Test with Answers helpful for self-assessment and preparation.
Class 10 AI Project Cycle MCQ
MCQ on AI Project Cycle Class 10
Class 10 AI Project Cycle MCQ – AI Project Cycle MCQ Class 10
Multiple Choice Questions:
Question 1.
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.
(a) Output layer
(b) Hidden layer
(c) Input layer
(d) Data layer
Answer:
(b) Hidden layer
Question 2.
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?
(a) Traditional programming
(b) Manual processing
(c) IoT
(d) Neural networks
Answer:
(d) Neural networks
Question 3.
For better efficiency of an AI project Training data should be ______ SQP
(i) Relevant
(ii) Scattered
(iii) Structured
(iv) Authentic
Choose the correct option:
(a) Both (i) and (ii)
(b) Both (i) and (iv)
(c) Only (i)
(d) Only (iv)
Answer:
(b) Both (i) and (iv)
Question 4.
The ________ Sustainaible Development Goals (SDGs) were launched at the, United Nations Sustainable Development Summit in New York in the year 2015, forming the 2030 Afsenda for Sustainable Development.
(a) 17
(b) 15
(c) 13
(d) 19
Answer:
(a) 17
Question 5.
Identify the algorith m based on the given graph
Or
Which form of unsupervised learning does the following diag, ram indicate?
(a) Dimensionality reduction
(b) Classification
(c) Clustering
(d) Regression
Answer:
(c) Clustering
Question 6.
Choose the five stages of AI project cycle in correct order
(a) Evaluation → Problem Scoping → Data Exploration → D ata Acquisition → Modelling
(b) Prclolem Scoping → Data Exploration → Data Ac quisition → Evaluation → Modelling
(c) Drita Acquisition → Problem Scoping → Data E xploration → Modelling → Evaluation
(d) Problem Scoping → Data Acquisition → Data Exploration → Modelling → Evaluation
Answer:
(d) Problem Scoping → Data Acquisition → Data Exploration → Modelling → Evaluation
Question 7.
A biisiness problem where in we categorize whether an ubservation is “Safe”, “AtRisk,” or “Unsafe” is an exismple of
(a) Classification
(b) Clustering
(c) Regression
(d) Dimensionality Reduction
Answer:
(a) Classification
Question 8.
_____ helps us to summarise all the key F ooints into one single outline so that in future, ‘whenever there is need to look back at the basis of the problem, we can take a look at it and understand the key elements of it.
(a) 4 Ws Problem canvas
(b) Problem Statement Template
(c) Data Acquisition
(d) Algorithm
Answer:
(b) Problem Statement Template
Question 9.
Which of the following is true about neural networks?
(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
Answer:
(a) Neural Networks tend to perform better with larger amounts of data.
Question 10.
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
Answer:
(b) Supervised learning
Question 11.
A _____ is divided into multiple layers and each layer is further divided into several blocks called nodes.
(a) Neural Networks
(b) Convolutional Neural Network (CNN)
(c) Machine learning algorithm
(d) Hidden Layers
Answer:
(a) Neural Networks
Question 12.
The _____ canvas helps you in identifying the key elements related to the problem.
(a) Problem scoping
(b) 4 Ws Problem
(c) Project cycle
(d) Algorithm
Answer:
(b) 4 Ws Problem
Question 13.
Name any two methods of collecting data.
(a) Surveys and Interviews
(b) Rumors and Myths
(c) AI models and applications
(d) Imagination and thoughts
Answer:
(a) Surveys and Interviews
Question 14.
Give two examples of Supervised Learning models.
(a) Classification and Regression
(b) Clustering and Dimensionality Reduction
(c) Rule Based and Learning Based
(d) Classification and Clustering
Answer:
(a) Classification and Regression
Question 15.
Which of the following is not part of the AI Project Cycle?
(a) Data Exploration
(b) Modelling
(c) Testing
(d) Problem Scoping
Answer:
(c) Testing
Question 16.
_____ is the last stage of the AI project life cycle.
(a) Problem Scoping
(b) Evaluation
(c) Modelling
(d) Data Acquisition
Answer:
(b) Evaluation
Question 17.
Which of the following contributes to the efficiency of an Al project?
(a) High Model Complexity
(b) Relevant and Authentic Training Data
(c) Minimal Preprocessing
(d) Limited Hardware Resources
Answer:
(b) Relevant and Authentic Training Data
Question 18.
What is the primary need for evaluating an Al model’s performance in the Al Model Development process?
(a) To increase the complexity of the model.
(b) To visualize the data.
(c) To assess how well the chosen model will work in future.
(d) To reduce the amount of data used for training.
Answer:
(c) To assess how well the chosen model will work in future.
Question 19.
The 4 W’s Problem Canvas helps in identifying the key elements related to the given problem.
Which of the following is not one of the blocks of the Problem Canvas?
(a) When
(b) What
(c) Where
(d) Why
Answer:
(a) When
Question 20.
During Data Acquisition, feeding previous data into the machine is called:
(a) Training Data
(b) Testing Data
(c) Predicting Data
(d) Evaluating Data
Answer:
(a) Training Data
Question 21.
Which 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.
Answer:
(c) They are modelled on human brains and nervous system.
Statement Based Questions:
Question 1.
Statement 1 There are four layers in a neural network.
Statement 2 The first layer of the neural network is known as the output layer.
(a) Both Statement 1 and Statement 2 are correct
(b) Both Statement 1 and Statement 2 are incorrect
(c) Statement 1 is correct but Statement 2 is incorrect
(d) Statement 2 is correct but Statement 1 is incorrect
Answer:
(b) Both Statement 1 and Statement 2 are incorrect
Question 2.
Statement 1 A neural network is a method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain.
Statement 2 It is a type of machine learning process, called deep learning, that uses interconnected nodes or neurons in a layered structure that resembles the human brain.
(a) Both Statement 1 and Statement 2 are correct
(b) Both Statement 1 and Statement 2 are incorrect
(c) Statement 1 is correct but Statement 2 is incorrect
(d) Statement 2 is correct but Statement 1 is incorrect
Answer:
(a) Both Statement 1 and Statement 2 are correct
Question 3.
Statement 1 Unsupervised learning uses labeled datasets to train algorithms to predict outcomes and recognize patterns.
Statement 2 In unsupervised learning, the training data provided to the machines work as the supervisor.
(a) Both Statement 1 and Statement 2 are correct
(b) Both Statement 1 and Statement 2 are incorrect
(c) Statement 1 is correct but Statement 2 is incorrect
(d) Statement 2 is correct but Statement 1 is incorrect
Answer:
(b) Both Statement 1 and Statement 2 are incorrect
Question 4.
Statement 1 Clustering is a machine learning technique, which groups the unlabeled dataset.
Statement 2 It is helpful for predicting numerical values based on different data points, such as sales revenue projections for a given business.
(a) Both Statement 1 and Statement 2 are correct
(b) Both Statement 1 and Statement 2 are incorrect
(c) Statement 1 is correct but Statement 2 is incorrect
(d) Statement 2 is correct but Statement 1 is incorrect
Answer:
(c) Statement 1 is correct but Statement 2 is incorrect
Assertion & Reason Based Questions:
Question 1.
Assertion (A) Neural networks are the backbone of deep learning algorithms
Reason (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
Answer:
(a) Both A and R are correct and R is the correct explanation of A
Question 2.
Assertion (A) We can use histograms when data is in categories (such as “Pop”, “Rock”, “Jazz”, “Hip-Hop” etc).
Reason (R) We use bar charts when we have continuous data (such as a person’s height or weight).
(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) Both A and R are incorrect
Answer:
(d) Both A and R are incorrect
Question 3.
Assertion (A) Data acquisition is the first step in the Al project cycle.
Reason (R) Data acquisition involves gathering relevant data from various sources to fuel subsequent stages of the AI project cycle, including data exploration, model development, and deployment.
(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
Answer:
(d) A is not correct but R is correct
Question 4.
Assertion (A) Supervised learning is a type of machine learning where the model is trained on labeled data.
Reason (R) In supervised learning, the model learns from input-output pairs, where each input data point is associated with a corresponding output label.
(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
Answer:
(a) Both A and R are correct and R is the correct explanation of A
Question 5.
Assertion (A) Neural networks are capable of learning complex patterns and relationships in data.
Reason (R) Neural networks consist of interconnected nodes, or neurons, organized in layers, which perform computations and transformations on the input 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
Answer:
(a) Both A and R are correct and R is the correct explanation of A
