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FinTech 10-1 Time Series

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

What were the objectives of Time Series Day 1?

a)

Manipulate time series data sets in pandas

b)

Perform auto-correlation on time series data

c)

Identify the components of a time series

d)

Time series analysis in Scikit-learn

e)

Analyze long term trends with different averages and filters

2.

Which are applications of machine learning?

a)

Determining loan eligibility

b)

Fraud and money laundering

c)

Designing a cryptocurrency

d)

Customer segmentation and clustering

e)

Disease diagnosis and prognosis

3.

Which are Python libraries that can be used for machine learning?

a)

Scikit-Learn

b)

TensorFlow

c)

NumPy

d)

SciPy

e)

Pandas

4.

Which are types of machine learning?

a)

Supervised learning

b)

Unsupervised learning

c)

Independent learning

d)

Reinforcement learning

5.

Which are type of machine learning is regression?

a)

Supervised learning

b)

Unsupervised learning

c)

Independent learning

d)

Reinforcement learning

6.

Which are type of machine learning is clustering?

a)

Supervised learning

b)

Unsupervised learning

c)

Independent learning

d)

Reinforcement learning

7.

Which steps should you take to prepare a time series dataframe?

a)

Read in the csv using pandas

b)

Format the x-axis as dates

c)

Set the index to the datetime column

d)

Set parse_dates = True

8.

Analogy - groupby : typical dataframes :: ______ : time series dataframes

a)

groupby()

b)

mean()

c)

resample()

d)

set_index()

9.

How was Time Series Day 1 for you?

4 lines
10.

Any suggestions for improvement?

4 lines