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.
Topics Covered
Answer Key Artificial Intelligence Class 10 Board Exam 2023
I have provided few sample papers 2023 for artificial intelligence and many questions have been asked from there as well as mock test. Let’s start now!
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
[2] GUI stands for :
a) Graphical User Interaction
b) Graphical User Interface
c) Graphical Upper Interface
d) None of these
[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
[4] Right, clicking on File or Folder opens
a) Main Menu
b) Shortcut Monu
c) Back Menu
d) Front 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
[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
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 _____________
[2] This is a fact that all human beings have all nine types of intelligences, but at different levels. Name any two such intelligences.
[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)
[4] During Data Acquisition, feeding previous data into the machine is called
a) Training Data
b) Predicting Data
c) Testing Data
d) Evaluating 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)
[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
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
[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
[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
[4] _________ helps to find the best model that represents our data and how well the chosen model will work in future.
[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)
[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
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.
[2] Two conditions when prediction matches with the reality are true positive and ____________
[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.
[4] With reference to Al domain, expand the term CV.
[5] Under ____________, One looks at various parameters which affect the problem we wish to solve, as this would make many lives better.
[6] In this learning model, the data set which is fed to the machine is labelled. Name the model.
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)
[2] When the prediction matches the reality, the condition is termed as _______________
[3] Smart Assistants such as Alexa, and Siri are examples of :
a) Natural Language Processing
b) Data Science
c) Machine Learning
d) Computer Vision
[4] 4Ws Problem Canvas is a part of :
a) Problem Scoping
b) Data Acquisition
c) Modelling
d) Evaluation
[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
[6] Which of the following talks about how true the preditions are by any model?
a) Accuracy
b) Reliability
c) Recall
d) F1 Score
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.
Q – 7 Give any two key roles performed by an entrepreneur.
Q – 8 Mention any two benefits of workng independently..
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.
Q – 10 Define the term agricultural entrepreneurship. How are farmers benefitted from it ?.
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.
Q – 12 What is dimensionality reduction?
Q – 13 Define chatbot. What are its types?
Q – 14 Define Confusion Matrix
Q – 15 Face lock feature of a smartphone is an example of computer vision. Briefly discuss this feature.
Q – 16 With reference to data processing, expand the term TFIDF. Also give any two applications of TFIDF.
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.
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.
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
