Predictive Analytics with TensorFlow 2.3: Using Information Theory in Predictive Modeling

Predictive Analytics with TensorFlow 2.3: Using Information Theory in Predictive Modeling

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video tutorial introduces information theory, highlighting its applications in various fields such as communication, medical science, and machine learning. It explains key concepts like mutual information, entropy, and information gain, and their roles in predictive modeling. The tutorial also covers the use of information theory in machine learning, particularly in decision trees and neural networks. Additionally, it introduces a Python module for implementing information theory concepts, providing examples of its application.

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7 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which field is NOT mentioned as a common application area for information theory?

Medical Science

Communication Engineering

Astrophysics

Psychology

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does mutual information measure?

The likelihood of independent events

The probability of a single event

The amount of information obtained about one random variable by observing another

The total entropy of a system

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the expected amount of information contained in a random variable called?

Mutual Information

Joint Entropy

Entropy

Conditional Entropy

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How is Shannon entropy expressed?

In units of joules

In units of hertz

In units of bits

In units of bytes

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of information gain in decision trees?

To reduce the number of nodes

To decide the best split or rule at each level

To increase the entropy of the system

To increase the complexity of the model

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the role of cross entropy in machine learning?

It is used to increase the entropy of a dataset

It is a method for data compression

It is used as a loss function in deep neural networks

It measures the accuracy of a model

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which Python module is mentioned for information theory applications?

Pandas

Did

SciPy

NumPy

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