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10. Which among the following is not a type of Machine Learning?

a. Reinforcement learning `b. Unsupervised learning
c. Convoluti onal Neural Networks d. Supervised learning

B. Fill in the blanks.
1. Deep learning is a subset of __________.
2. Object identification and localisation are examples of __________ learning.

3. The __________ dataset is a collection of examples given to the model to analyse and learn.
4. A drawback or rule-based AI model is that is __________ in nature.
5. Supervised, unsupervised, and reinforcement learning are categories of __________ models.
6. Supervised learning requires __________ data to train a model.
7. An AI model that groups similar data points without prior labels is performing __________ learning.

8. The __________ algorithm is the simplest type of artificial neural network used for binary classification.
9. In reinforcement learning, the AI agent learns by receiving __________ and __________ for its actions.
10. In regression tasks, the target variable is __________ rather than categorical.

C. State ‘T’ for True or ‘F’ for False statements.
1. Artificial Intelligence (AI) is the same as Machine Learning (ML).
2. Rule-based AI systems rely on predefined rules rather than learning from data.
3. Supervised learning requires labelled data for training a model.
4. Unsupervised learning is best suited for tasks like clustering and anomaly detection.

5. Rule-based learning is used to train models that require decision-making in dynamic environments.
6. Classification and regression models both deal with categorical output variables.
7. Convolutional Neural Networks (CNNs) are primarily used for image recognition tasks.

8. Deep learning models typically require more data and computational power than traditional machine
learning models.

9. Association rule learning is used to find relationships between variables in large datasets, such as market
basket analysis.

10. AI models always provide 100% accurate predictions once trained on a dataset.
D. Very short answer type questions.
1. What is Artificial Intelligence (AI)?
2. Define Machine Learning (ML).

3. What is the main goal of Deep Learning?
4. How does a rule-based AI system function?
5. Name the three main types of machine learning.

6. What is the key difference between classification and regression models?
7. What type of learning does a clustering algorithm use?
8. What does CNN stand for in deep learning?
9. What is the role of labels in supervised learning?
10. Name one common application of reinforcement learning.

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