Databricks Databricks-Certified-Professional-Data-Scientist Quiz 1 Topic 6 Questions 1-5

Question: 1

Reducing the data from many features to a small number so that we can properly visualize it in

two or three dimensions. It is done in_______

Asupervised learning

Bun-supervised learning

Ck-Nearest Neighbors

DSupport vector machines
The opposite of supervised learning is a set of tasks known as unsupervised learning. In unsupervised learning, there's no label or target value given for the data. A task where we group similar items together is known as clustering. In unsupervised learning, we may also want to find statistical values that describe the data. This is known as density estimation. Another task of unsupervised learning may be reducing the data from many features to a small number so that we can properly visualize it in two or three dimensions

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Question: 2

In which of the following scenario you should apply the Bay's Theorem

AThe sample space is partitioned into a set of mutually exclusive events {A1, A2, . .., An }.

BWithin the sample space, there exists an event B, for which P(B) > 0.

CThe analytical goal is to compute a conditional probability of the form: P(Ak | B ).

DIn all above cases

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Question: 3

Scenario: Suppose that Bob can decide to go to work by one of three modes of transportation,

car, bus, or commuter train. Because of high traffic, if he decides to go by car. there is a 50% chance he will be late. If he goes by bus, which has special reserved lanes but is sometimes overcrowded, the probability of being late is only 20%. The commuter train is almost never late, with a probability of only 1 %, but is more expensive than the bus.

Suppose that Bob is late one day, and his boss wishes to estimate the probability that he drove to work that day by car. Since he does not know Which mode of transportation Bob usually uses, he gives a prior probability of 1 3 to each of the three possibilities. Which of the following method the boss will use to estimate of the probability that Bob drove to work?

ANaive Bayes

BLinear regression

CRandom decision forests

DNone of the above
Bayes' theorem (also known as Bayes' rule) is a useful tool for calculating conditional probabilities.

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Question: 4

Spam filtering of the emails is an example of

ASupervised learning

BUnsupervised learning

CClustering

D1 and 3 are correct

E2 and 3 are correct
Clustering is an example of unsupervised learning. The clustering algorithm finds groups within the data without being told what to look for upfront. This contrasts with classification, an example of supervised machine learning, which is the process of determining to which class an observation belongs. A common application of classification is spam filtering. With spam filtering we use labeled data to train the classifier: e-mails marked as spam or ham.

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Question: 5

Which of the following problem you can solve using binomial distribution

AA manufacturer of metal pistons finds that on the average: 12% of his pistons are rejected because they are either oversize or undersize. What is the probability that a batch of 10 pistons will contain no more than 2 rejects?

BA life insurance salesman sells on the average 3 life insurance policies per week. Use Poisson's law to calculate the probability that in a given week he will sell Some policies

CVehicles pass through a junction on a busy road at an average rate of 300 per hour Find the probability that none passes in a given minute.

DIt was found that the mean length of 100 parts produced by a lathe was 20.05 mm with a standard deviation of 0.02 mm. Find the probability that a part selected at random would have a length between 20.03 mm and 20.08 mm
The entire problem can be solved using below method
Binomial: A manufacturer of metal pistons finds that on the average, 12% of his pistons are rejected because they are either oversize or undersize. What is the probability that a batch of 10 pistons will contain no more than 2 rejects?
Poisson: A life insurance salesman sells on the average 3 life insurance policies per week. Use Poisson's law to calculate the probability that in a given week he will sell Some policies
Poisson: Vehicles pass through a junction on a busy road at an average rate of 300 per hour Find the probability that none passes in a given minute.
Normal: It was found that the mean length of 100 parts produced by a lathe was 20.05 mm with a standard deviation of 0.02 mm. Find the probability that a part selected at random would have a length between 20 03 mm and 20.08 mm

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Databricks Databricks-Certified-Professional-Data-Scientist Quiz:1 Topic:6 Questions:1-5