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FinTech 10-1 Time Series

Authored by Louis Burns

Computers, Other

Professional Development

Used 12+ times

FinTech 10-1 Time Series
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10 questions

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1.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

What were the objectives of Time Series Day 1?

Manipulate time series data sets in pandas

Perform auto-correlation on time series data

Identify the components of a time series

Time series analysis in Scikit-learn

Analyze long term trends with different averages and filters

2.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

Which are applications of machine learning?

Determining loan eligibility

Fraud and money laundering

Designing a cryptocurrency

Customer segmentation and clustering

Disease diagnosis and prognosis

3.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

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

Scikit-Learn

TensorFlow

NumPy

SciPy

Pandas

4.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

Which are types of machine learning?

Supervised learning

Unsupervised learning

Independent learning

Reinforcement learning

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which are type of machine learning is regression?

Supervised learning

Unsupervised learning

Independent learning

Reinforcement learning

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which are type of machine learning is clustering?

Supervised learning

Unsupervised learning

Independent learning

Reinforcement learning

7.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

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

Read in the csv using pandas

Format the x-axis as dates

Set the index to the datetime column

Set parse_dates = True

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