Page 216 - AI Ver 3.0 class 10_Flipbook
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SECTION B (Subjective Type Questions)
A. Short answer type questions.
1. Why is the rule-based approach considered static?
2. What is a major advantage of the learning-based approach over the rule-based approach?
3. What is the primary difference between Clustering and Classification?
4. Explain the term Convolutional Neural Networks (CNN).
5. What do you mean by a Testing Dataset?
6. Name any four real-world applications of Neural Network.
B. Long answer type questions.
1. Explain the three basic layers of Artificial Neural Network.
2. Explain any four applications of machine learning in our daily lives.
3. Differentiate between supervised and unsupervised learning models.
4. Explain the term association rule with the help of an example.
5. What is regression? Give an example.
21 st Century #Information Literacy
C. Competency-based/Application-based questions. Skills #Critical Thinking
1. Identify the type of learning (supervised, unsupervised, reinforcement learning) are the following case studies most
likely based on?
a. Case Study 1: A car rental company wants to predict the rental price of vehicles based on features such as car type,
rental duration, and location. They have historical rental data with labelled prices.
b. Case Study 2: An online game uses a system where players are rewarded for making progress in the game and
penalized for making mistakes. The system learns the best strategies by interacting with players over time.
c. Case Study 3: A robot is learning to navigate a maze by receiving rewards for reaching the goal and penalties for
hitting walls, adjusting its actions based on this feedback.
d. Case Study 4: A company wants to identify potential fraudsters by analyzing transaction patterns and customer
behaviours, using labelled data of legitimate and fraudulent transactions.
e. Case Study 5: A library wants to analyse patterns in book loans to recommend books to patrons, without predefined
categories or labels for the books.
2. A retail store has a dataset containing transaction histories, customer demographics, purchase frequency, and product
categories. The tasks involve:
a. To predict whether a customer will make a purchase during a promotional campaign.
b. To forecast the total revenue for the next month.
c. To segment customers based on their purchasing behaviour for targeted marketing.
d. To discover frequently purchased product combinations for better shelf placement and promotions.
3. Identify the type of learning (supervised, unsupervised, reinforcement learning) are the following case studies most
likely based on?
Case Study 1: A company wants to predict customer churn based on past purchasing behaviour, demographics, and
customer interactions. They have a dataset with labelled examples of customers who churned and those who did not.
Case Study 2: A social media platform wants to group users based on their interests and behaviour to recommend
relevant content. They have a large dataset of user interactions but no predefined categories. Which type of learning is
this case study most likely based on?
214 Touchpad Artificial Intelligence (Ver. 3.0)-X

