Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Machine Learning Occa

Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Machine Learning Occa

Assessment

Interactive Video

Computers

10th - 12th Grade

Hard

Created by

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7 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary context in which Occam's Razor is explained in the video?

Clustering algorithms

Reinforcement learning

Unsupervised learning

Function modeling in supervised learning

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In a linear model with a single feature, what is the main limitation discussed?

It is too flexible

It cannot handle multiple features

It lacks flexibility

It requires too many parameters

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does adding more parameters to a model affect its flexibility?

It simplifies the model

It increases flexibility

It makes the model less adaptable

It decreases flexibility

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a potential downside of using a highly flexible model?

It simplifies the data

It can lead to overfitting

It reduces the number of parameters

It may not fit the data well

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

According to Occam's Razor, which model should be preferred if two models perform equally well?

The model with the highest accuracy

The simpler model

The more complex model

The model with more parameters

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does Occam's Razor suggest about the number of parameters in a model?

More parameters are always better

The number of parameters does not matter

Fewer parameters are preferred

Parameters should be maximized for flexibility

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main problem with a model that fits the data perfectly?

It is always the best choice

It is too simple

It may not generalize well

It has too few parameters