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Basics of Machine Learning

Authored by Aditi Rao

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University

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Basics of Machine Learning
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11 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is machine learning?

Machine learning is a method of data analysis that automates analytical model building.

Machine learning is a programming language for software development.

Machine learning is a type of hardware used for data storage.

Machine learning is a process of manual data entry and analysis.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Name one common application of machine learning.

Data cleaning

Recommendation systems

Image formation

data processing

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the difference between supervised and unsupervised learning?

Supervised learning is used for clustering, while unsupervised learning is used for classification.

Supervised learning uses labeled data for training, while unsupervised learning uses unlabeled data to find patterns.

Supervised learning requires no data for training, while unsupervised learning requires labeled data.

Supervised learning is faster than unsupervised learning regardless of data size.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a dataset in the context of machine learning?

A dataset is a structured collection of data used for training and testing machine learning models.

A dataset is a random collection of data points without any structure.

A dataset is a type of algorithm used in machine learning.

A dataset is a single data point used for making predictions.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a feature in machine learning?

A feature is the output of a machine learning model.

A feature is a type of machine learning algorithm.

A feature is an individual measurable property or characteristic used as input for a machine learning model.

A feature is a dataset used for training a model.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Explain the term 'training' in machine learning.

Training involves only testing the model's performance.

Training is the process of collecting data for analysis.

Training is the final step before deploying a model.

Training in machine learning is the process of teaching a model to learn from data by adjusting its parameters.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What role does a model play in machine learning?

A model in machine learning is used to make predictions or decisions based on input data.

A model is used to store data permanently.

A model helps in data cleaning and preprocessing.

A model is primarily for visualizing data trends.

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