quizz

In machine learning, what is a “model”?

• A type of computer

• A set of algorithms that learn data patterns to make predictions/decisions

• A mathematical equation

• A type of data visualization

Which of the following is an example of supervised learning?

• Clustering

• Regression

• Principal Component Analysis (PCA)

• Dimensionality Reduction

What is a “dataset”?

• A collection of data used to train and test a machine learning model

• A programming language

• A statistical tool

• A collection of data used to train and test a machine learning model

What is the primary goal of data science?

• To build mobile applications

• To analyze and interpret complex data to make informed decisions

• To write computer programs

• To create websites

What is “overfitting” in machine learning?

• When a model is too simple and doesn’t capture the data well

• When a model performs well on training data but poorly on new data

• When a model is too complex to run

• When a model is trained with too much data

What is a "classifier" in machine learning?

• A tool to sort data into categories

• A type of regression model

• A function to clean data

• A data visualization technique

What is the primary goal of data collection in a data science project?

• To clean the data

• To gather relevant data for analysis

• To split the data into training and testing sets

• To visualize the data

What does data cleaning involve?

• Removing irrelevant features

• Normalizing the data

• Handling missing values and correcting inaccuracies

• Selecting the best model

What does model evaluation measure?

• The quality of the data

• How well the model performs on unseen data

• The complexity of the model

• The amount of data collected

What is the purpose of data splitting in machine learning?

• To remove duplicates from the dataset

• To divide data into training and testing sets to evaluate model performance

• To perform feature selection

• To tune the model’s hyperparameters