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5. What does unsupervised learning primarily aim to achieve?
a. Predict specific labels for new data b. Identify hidden patterns or clusters in the data
c. Replace rule-based systems entirely d. Solve predefined problems using training data
6. Which of the following is NOT a sub-category of supervised learning? [CBSE Sample Paper, 2021]
a. Classification b. Regression
c. Clustering d. Predictive Modelling
7. Which of the following is an example of reinforcement learning?
a. Identifying spam emails
b. Predicting house prices
c. A robot learning to pick objects through trial and error
d. Grouping customers based on purchase history
8. Which of these is an example of a classification problem?
a. Predicting house prices b. Grouping customers based on spending
c. Determining if an email is spam d. Predicting the temperature
B. Fill in the blanks.
1. The learning-based approach is typically used when the dataset is ……….……................ and too random.
2. The goal of ……….……................ learning is to find hidden patterns or clusters in the data.
3. Supervised learning models use a ……….……................ dataset to train the machine.
4. Classification models work with ……….……................ datasets, whereas regression models predict ……….……................ values.
5. Neural Networks are able to extract data ……….……................ automatically without needing the input of the programmer.
6. ……….……................ are made up of layers of neurons, just like the human brain that consists of millions of neurons.
7. An ……….……................ in its training phase is capable of learning by recognising patterns in data which is later used to
generate the desired output.
8. The layer present in-between input and output layers is called the ……….……................ which perform most of the
computations required by our network.
C. State whether these statements are true or false.
1. A clustering algorithm is applied to group customers based on their purchase behaviour. ……….……
2. With AI, it’s not possible for machines to learn from the experience. ……….……
3. ANN is made up of two basic layers – Input and Output. ……….……
4. A labelled dataset is the information which is tagged with identifiers of data. ……….……
5. The data that is used to predict the model is called testing data. ……….……
6. Association rule is used in supervised learning to label datasets. ……….……
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).
138 Artificial Intelligence Play (Ver 1.0)-X

