Big Data Analytics Quiz 5

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Big Data Analytics Mastery Quiz

Test your knowledge and understanding of Big Data Analytics with our comprehensive quiz! This quiz consists of 11 multiple-choice questions that cover fundamental concepts and techniques in data science.

Explore key topics like k-means clustering, principal component analysis, and regression analysis.
Perfect for students, professionals, and enthusiasts looking to sharpen their skills.

11 Questions3 MinutesCreated by DataDive007

Place the four key steps in a data science study in the correct sequence:

1. Prepare data, 2. Select algorithms to model the data, 3. Tune algorithms to optimize the data, 4. Evaluate models based on accuracy

1. Prepare data, Tune algorithms to optimize data, 3. Evaluate models based on accuracy, 4. Select algorithms to model the data

1. Select algorithms to model the data, 2. Prepare data, 3. Tune algorithms to optimize the models, 4. Evaluate models based on accuracy

1. Evaluate models based on accuracy, 2. Prepare data, 3. Tune algorithms to optimize the models, 4. Select algorithms to model the data

What is k-means clustering?

Group items in distinct clusters, where ? Represents the # of clusters identifed

Find underlying variables that best differentiate your data points. These variables are dimensions along which your data points are most spread out.

An ensemble of decision trees, combining models of different strengths & weaknesses, to improve prediction accuracy.

Improve predictions by accounting for multiple predictors, and compare the strength of each predictor (e.g. In a best-fit line)

What is principal component analysis?

Group items in distinct clusters, where ? Represents the # of clusters identifed

Find underlying variables that best differentiate your data points. These variables are dimensions along which your data points are most spread out.

An ensemble of decision trees, combining models of different strengths & weaknesses, to improve prediction accuracy.

Improve predictions by accounting for multiple predictors, and compare the strength of each predictor (e.g. In a best-fit line)

What is a random forest model?

Group items in distinct clusters, where ? Represents the # of clusters identifed

Find underlying variables that best differentiate your data points. These variables are dimensions along which your data points are most spread out.

An ensemble of decision trees, combining models of different strengths & weaknesses, to improve prediction accuracy.

Improve predictions by accounting for multiple predictors, and compare the strength of each predictor (e.g. In a best-fit line)

What is regressions analysis?

Group items in distinct clusters, where ? Represents the # of clusters identifed

Find underlying variables that best differentiate your data points. These variables are dimensions along which your data points are most spread out.

An ensemble of decision trees, combining models of different strengths & weaknesses, to improve prediction accuracy.

Mprove predictions by accounting for multiple predictors, and compare the strength of each predictor (e.g. In a best-fit line)

What is the definition of unsupervised learning?

Tell me what patterns exist in my data.

Use the patterns in my data to make predictions.

Use the patterns in my data to make predictions; improving predictions as more results come in.

What is the definition of supervised learning?

Tell me what patterns exist in my data.

Use the patterns in my data to make predictions.

Use the patterns in my data to make predictions; improving predictions as more results come in.

What is the definition of reinforcement learning?

Tell me what patterns exist in my data.

Use the patterns in my data to make predictions.

Use the patterns in my data to make predictions; improving predictions as more results come in.

Big Data Analytics Quiz 5

Big Data Analytics Mastery Quiz

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