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4. ___________ can check whether an email is spam or not.
a. Anomaly detection b. Regression algorithm

c. Both a and b d. None of these 4. a b c d

5. ___________ algorithm will be needed to predict the
temperature on next Monday.
5. a b c d
a. Regression b. Clustering
c. Anomaly detection d. Reinforcement

6. ___________ is a type of machine learning that is based on 6. a b c d
rewards and punishment.

a. Reinforcement b. Clustering learning
c. Anomaly detection d. Regression
B. Gap-fill exercise.

1. ____________ is an intelligent decision-making process with the help of historical data.

2. ____________ is the process of training a machine to make decisions just like a human
brain.
3. A ____________ is a specialist who uses information to provide insights.

4. ____________ are responsible for anticipating the future demands of an organisation.
5. If the number of output classes is two, then the classification is called ____________ .

6. An ____________ means an object whose features are not similar to those of other
objects in a particular group.
C. True and False assessment.
1. Data should be filtered before processing.

2. Data science helps with prediction of the future and the optimising of resources.
3. If the relevant data is not available, you can generate any predictions.

4. To understand data in a better manner, different visualisation techniques must be
used.
5. Data Analysts are responsible for anticipating the future demands of the
organisation.
6. Regression algorithms in machine learning are used to answer many kinds of
questions.

D. Give appropriate responses to the questions.
1. What is the data science?

2. Why is data science important?
3. What are the tasks of a data scientist?

4. What are outliers? Give an example.
5. List any five applications of data science.

6. Discuss the various sources of data science.

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