In this article, I am going to provide you with answer Key Artificial Intelligence Class 10 Board Exam 2023. This mock test help you to score good marks in your board exam of Artificial Intelligence Class 10. Here we go!
This answer key is prepared after discussion with subject experts. This is not an official board answer key. All answers are suggested answers and your answers will be evaluated by board official marking scheme.
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Answer Key Artificial Intelligence Class 10 Board Exam 2023
I have provided a few sample papers 2023 for artificial intelligence, and many questions have been asked from there, as well as a mock test. Let’s start now!
Watch this video to understand its practicality!!!
Section [A] Objective Type Questions – Answer Key Artificial Intelligence Class 10 Board Exam 2023
Q -1 Answer any 4 out of the given 6 questions on Employability Skills (1 x 4 = 4 marks)
[1] Which of the following is not a task of an entrepreneur?
a) Sharing of wealth
b) Preferably using foreign materials
c) Fulfilling customer needs
d) Helping society
Ans.: b) Preferbly using foreign materials
[2] GUI stands for :
a) Graphical User Interaction
b) Graphical User Interface
c) Graphical Upper Interface
d) None of these
Ans.: b) Graphical User Interface
[3] Which of the following is a function of an entrepreneur?
a) Following the traditional method of business
b) Innovation
c) Keeping all the profit to himself/herself
d) Avoid taking decisions
Ans.: b) innovation
[4] Right, clicking on File or Folder opens
a) Main Menu
b) Shortcut Monu
c) Back Menu
d) Front Menu
Ans.: b) Shortcut Menu
[5] Stress management is vital because it leads to following benefits
a) Improves mood
b) Boosts Immune System
c) Promotes longevity
d) All of the above
Ans.: d) All od the above
[6] Which of the following is an inner urge to do something, achieve their goals without any external pressure / lure for award or appreciation?
a) Self-awareness
b) Self-motivation
c) Self-regulation
d) Self-control
Ans.: b) Self-Motivation
Q.2. Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
[1] Two popular examples of pocket assistants are _____________ and _____________
Ans.: Apple Siri, Google Assistant, Microsoft Cortana, Amazon Alexa
[2] This is a fact that all human beings have all nine types of intelligences, but at different levels. Name any two such intelligences.
Ans.: Mathematical Logical reasoning, Linguistic Intelligence, Spatial Visual Intelligence, Kinesthetic Intelligence, Musical Intelligence, Intrapersonal Intelligence, Existantial Intelligence, Naturalist Intelligence, Interpersonal Intelligence
[3] Identify the incorrect statements from the following :
i) Al models can be broadly categorized into four domains.
ii) Data sciences is one of the domain of Al model.
iii) Price comparison websites are examples of data science.
iv) The information extracted through data science can be used to make decision about it.
a) Only (iv)
b) (iii) and (iv)
c) Only (i)
d) (ii) and (iii)
Ans.: c) Only (i)
[4] During Data Acquisition, feeding previous data into the machine is called
a) Training Data
b) Predicting Data
c) Testing Data
d) Evaluating Data
Ans.:a) Training Data
[5] 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)
Ans.: False
[6] Which of the following is defined as the measure of balance between precision and recall ?
a) Accuracy
b) F1 Score
c) Reliability
d) Punctuality
Ans.: b) F1 Score
Q. 3 Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
[1] Email filters, spam filters, smart assistants are the examples of :
a) Pocket Assistants
b) CV
c) NLP
d) Evaluation
Ans.: c) NLP
[2] Select the correct features of Smart Bot :
a) Smart-bots are flexible and powerful
b) Coding is required to take this up on board
c) Smartbots work on bigger database and other resources directly
d) All of the above
Ans.: d) All of the above
[3] For ___________ the whole corpus is divided into sentences. Each sentence is taken as a different data so now the whole corpus gets reduced to sentences.
a) Text Regulation
b) Sentence Segmentation
c) Tokenisation
d) Stemming
Ans.: b) Sentence Segmentation
[4] _________ helps to find the best model that represents our data and how well the chosen model will work in future.
Ans.: Evaluation
[5] While evaluating a model’s performance, recall parameter considers
i) False positive
ii) True positive
iii) False negative
iv) True negative
Choose the correct option: 1
a) only (i)
b) (ii) and (iii)
c) (iii) and (iv)
(d) (i) and (iv)
Ans.: b) (ii) and (iii)
[6] With reference to NLP, consider the following plot of occurrence of words versus their value :
In the given graph, X represents :
a) Rare / valuable words
b) Punctuation words
c) Popular words
d) Pronoun
Ans.: a) Rare/Valuable Words
Q. 4 Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
[1] Which of the following is a feature of document classification?
a) Helps in classifying the type and genre of a document,
b) Helps in creating a document,
c) Helps to display important information of a corpus.
d) Helps in including the necessary words in the text body.
Ans.: a) Helps in classifying the type and genre of a document
[2] Two conditions when prediction matches with the reality are true positive and ____________
Ans.: true negative
[3] 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.
Ans.: c) They are modelled on humans brains and nervous system
[4] With reference to Al domain, expand the term CV.
Ans.: Computer Vision
[5] Under ____________, One looks at various parameters which affect the problem we wish to solve, as this would make many lives better.
Ans.: Problem Scoping
[6] In this learning model, the data set which is fed to the machine is labelled. Name the model.
Ans.: Supervised Learning
Q. 5 Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
[1] _______________ is a term used for any word or number or special character occurring in a sentence. (Token / Punctuator)
Ans.: Token
[2] When the prediction matches the reality, the condition is termed as _______________
Ans.: True Positive
[3] Smart Assistants such as Alexa, and Siri are examples of :
a) Natural Language Processing
b) Data Science
c) Machine Learning
d) Computer Vision
Ans.: a) Natural Language Processing
[4] 4Ws Problem Canvas is a part of :
a) Problem Scoping
b) Data Acquisition
c) Modelling
d) Evaluation
Ans.: a) Problem scoping
[5] It 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
Ans.: c) Clustering
[6] Which of the following talks about how true the preditions are by any model?
a) Accuracy
b) Reliability
c) Recall
d) F1 Score
Ans.: a) Accuracy
Section [B] Subjective Type Questions
Answer any 3 out of the given 5 questions on Employability Skills (2 x 3 = 6 marks)
Answer each question in 20 – 30 words.
Q – 6 How do mdeitation help in Managing Stress? Discuss briefly.
Ans.:
Meditation is a practice where an individual is supposed to focus his/her mind on a particular object, thought or activity to achieve a calm mental state reducing stress.
Q – 7 Give any two key roles performed by an entrepreneur.
Ans.
Innovator’s Role: Entrepreneurs innovate by bringing unique and new products and services into the market. In many cases, these are improved versions of existing products or services available. Innovation fuels economic growth and helps to boost global presence of products and services.
Agent’s role: Entrepreneurs act as ‘Agents of Change’ as they identify opportunities, solve problems, offer effective solutions, establish enterprises, set up industries and bring positive change for the economy.
Q – 8 Mention any two benefits of workng independently..
Ans.:
• Ensures greater learning.
• Individuals feel more empowered and responsible.
• It provides flexibility to choose and define working hours and working mechanisms.
• Failure and success of the task assigned are accounted by individuals.
• Individuals become assets to organizations, groups and nations at large.
• It ensures creativity and satisfaction amongst individuals.
Q – 9 Gurmeet has just bought a new computer for his offce. Suggest him any two points which he should keep in mind to prevent his computer from viras infection.
Ans.:
• Install and use anti-virus software.
• Keep anti-virus software updated.
• Scan all the files that you download from the Internet
• Do not open e-mails of an unknown person/sender
• Don’t allow any untrustworthy person to use your system.
• New use unknown pen drive/CD on your computer
• Never click on the windows that pop-up when you are surfing the Internet.
Q – 10 Define the term agricultural entrepreneurship. How are farmers benefitted from it ?.
Ans.:
Agricultural Entrepreneurship can be defined as being primarily related to the marketing and production of inputs and products used in agricultural activities. Farmers have benefited the most with rise in agricultural entrepreneurship as it has led to low-cost innovations in farming processes.
Answer any 4 out of the given 6 questions in 20 – 30 words each (2 x 4 = 8 marks)
Q – 11 Explain any one example of AI bias.
Ans.:All the virtual assistants have a female voice. It is only now that some companies have understood this bias and have started giving options for male voices but since the virtual assistants came into practice, female voices are always preferred for them over any other voice.
Q – 12 What is dimensionality reduction?
Ans.: Dimensionality reduction refers to reduce the dimensions of object and still be able to make sense out of the data. It reduces the dimension without losing any information in dimensionality reduction.
Q – 13 Define chatbot. What are its types?
Ans.: A chatbot is a computer program that uses artificial intelligence (AI) and natural language processing (NLP) to understand customer questions and automate responses to them, simulating human conversation.
There are two kinds of chatbot:
1. Smartbot
2. Chatbot
Q – 14 Define Confusion Matrix
Ans.: The result of comparison between the prediction and reality can be recorded in what we call the confusion matrix. The confusion matrix allows us to understand the prediction results.
Q – 15 Face lock feature of a smartphone is an example of computer vision. Briefly discuss this feature.
Ans.: Smartphones nowadays come with the feature of face locks in which the smartphone’s owner can set up his/her face as an unlocking mechanism for it. The front camera detects and captures the face and saves its features during initiation. Next time onwards, whenever the features match, the phone is unlocked.
Q – 16 With reference to data processing, expand the term TFIDF. Also give any two applications of TFIDF.
Ans.: TFIDF stands for Term Frequency and Inverse Document Frequency.
Some applications of TFIDF are:
1. Document Classification
2. Topic Modelling
3. Information Retrieval System
4. Stop Word Filtering
Answer any 3 out of the given 5 questions in 50– 80 words each (4 x 3 = 12 marks)
Q – 17 Ms. 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 times, these terms are used interchangeably but are they the same? Justify your answer. Help her in understanding these terms by drawing a well-labeled diagram to depict the interconnection between these three fields.
Artificial Intelligence
Artificial Intelligence (AI) Refers to any technique that enables computers to mimic human intelligence. It gives the ability to machines to recognize a human’s face; move and manipulate objects; understand voice commands by humans, and also do other tasks. The AI-enabled machines think algorithmically and execute what they have been asked for intelligently.
Machine Learning (ML)
It is a subset of Artificial Intelligence which enables machines to improve at tasks with experience (data). The intention of Machine Learning is to enable machines to learn by themselves using the provided data and make accurate Predictions/ Decisions.
Deep Learning (DL)
It enables software to train itself to perform tasks with vast amounts of data. In Deep Learning, the machine is trained with huge amounts of data which helps it in training itself around the data. Such machines are intelligent enough to develop algorithms for themselves. Deep Learning is the most advanced form of Artificial Intelligence out of these three. Then comes Machine Learning which is intermediately intelligent and Artificial Intelligence covers all the concepts and algorithms which, in some way or the other mimic human intelligence.
There are a lot of applications of AI out of which few are those which come under ML out of which very few can be labeled as DL. Therefore, Machine Learning (ML) and Deep Learning (DL) are part of Artificial Intelligence (AI), but not everything that is Machine learning will be Deep learning.
Q – 18 What is the significance of the Al project cycle? Also, explain in detail About how Data Acquisition is different from data exploration.
Ans.: The AI Project Cycle provides us with an appropriate framework which can lead us towards the goal. The AI Project Cycle mainly has 5 stages:
1. Problem Scoping
2. Data Acquisition
3. Data Exploration
4. Modelling
5. Evaluation
Data Acquisition: It is a process of acquiring data from various source. Data can be collected thorugh surveys, interviews, webscrapping, sensors, cameras, obersvation, and API programs. Data is collected before data collection. The data which is fed into the model is training data and prediction data is testing data.
Data Exploration: In data acquisition data which are collected may be complex. So data exploration is used to make some pattern from data or visualiza the data in a proper format. Here the data will be represeneted through various graphs and visualization forms.
Q – 19 Create a document vector table from the following documents by implementing all the four steps of Bag of words model. Also depict the outcome of each step.
Document 1 : Sameera and Sanya are classmates.
Document 2 : Sameera likes dancing but Sanya loves to study mathematics.
Ans.:
Step 1: Collecting data and processing it
Document 1: Sameera and Sanya are classmates
Document 2: Sameera likes dancing but Sanya loves to study mathematics
After text normalization the text becomes:
Document 1: [Sameera, and, Sanya, are , classmates]
Document 2: [Sameera, likes, dancing, but, Sanya, loves, to, study , mathematics]
Step 2: Create a Dictionary
| Sameera | and | Sanya | are | classmates | likes |
| dancing | but | loves | to | study | mathematics |
Step 3 : Create a Document Vector
| Sameera | and | Sanya | are | classmates | likes | dancing | but | loves | to | study | mathematics | |
| D1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Step 4: Repeat for all documents
| Sameera | and | Sanya | are | classmates | likes | dancing | but | loves | to | study | mathematics | |
| D1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| D2 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
Q – 20 Will it be valid to say that not all the devices which are termed as smart are Al-enabled? Justify this statement. Explain any two examples from daily life which are commonly misunderstood as Al.
Ans.: No, not all the devices which are termed as Smart are AI enables. any machine that has been trained with data and can make decisions/predictions on its own can be termed as AI. Here, the term ‘training’ is important.
Example 1:
A fully automatic washing machine can work on its own, but it requires human intervention to select the parameters of washing and to do the necessary preparation for it to function correctly before each wash, which makes it an example of automation, not AI.
Example 2:
An air conditioner can be turned on and off remotely with the help of internet but still needs a human touch. This is an example of Internet of Things (IoT). Also, every now and then we get to know about robots which might follow a path or maybe can avoid obstacles but need to be primed accordingly each time.
Just as humans learn how to walk and then improve this skill with the help of their experiences, an AI machine too gets trained first on the training data and then optimises itself according to its own experiences which makes AI different from any other technological device/machine.
Q – 21 Recently the country was shaken up by a series of earthquakes which has done a huge damage to the people as well as the infrastructure. To address this issue, an Al model has been created which can predict if there is a chance of earthquake or not. The confusion matrix for the same is :
(ii) Calculate precision, recall and F1 score.
Ans.:
(i) There are 20 Negative cases in the above scenario.
(ii) To calculate precision we need True Positive cases and All predicted positives. So
True Positive – 50
False Positive – 05
precision = TP/(TP+FP)*100%=50/(50+5)*100%=50/55*100%=0.91
For recall, we need True Positive and False Negative which are 50 and 25.
recall=TP/(FP+FN)=50/(50+25)=50/75=0.67
F1 score= 2*((precision*recall)/(precision+recall))=2*((0.91*06.7)/(0.91+0.67))=2*(0.6097/1.58)=2*0.386=0.772
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