How much do you know about machine learning?

You hear a lot about machine learning these days. But how does it actually work?

 

Take the quiz — just 10 questions — to see how much you know about machine learning!

QUESTION 01

What type of machine learning algorithm makes predictions when you have a set of input data and you know the possible responses?

Supervised learning
Supervisory logic
Unsupervised learning
Deep learning

QUESTION 02

What category of machine learning algorithm finds patterns in the data when the data is not labeled?

Data prophecy
Unsupervised learning
Supervisory logic
Supervised learning

QUESTION 03

When would you reduce dimensions in your data?

When the data comes from sensors
When you’re using a Linux machine
When your data set is larger than 500 GB

When you have a large set of features with similar characteristics

QUESTION 04

What does a classification model do?

Predicts real number responses such as changes in temperature, date, or time

Assigns data to a predefined category

Clusters responses in groups based on similarity, to find patterns
Compares predicted data classifications to the actual class labels in the data 

QUESTION 05

Which one of these classification algorithms is easiest to start with for prediction?

Naïve Bayes

Neural network

Logistic regression
Bagged decision tree

QUESTION 06

What does hyperparameter tuning do?

Optimizes parameters to improve performance of a learning algorithm
Specifies the hyperplane that represents linear classifiers
Expands the parameter set of a model to improve performance
Takes parameter tuning so far that performance degrades

QUESTION 07

Which feature selection technique uses shrinkage estimators to remove redundant features from data?

Stepwise regression
Sequential feature selection
Neighborhood component analysis
Regularization

QUESTION 08

What is principal component analysis?

A feature selection technique that adds or removes features to optimize prediction accuracy
A linear feature transformation technique for reducing data dimensionality
A clustering technique that partitions data into mutually exclusive clusters
A predictive technique that identifies a better set of parameters 
overfitting

QUESTION 09

What is overfitting?

When a predictive model is accurate but takes too long to run
When the model learns specifics of the training data that can’t be generalized to a larger data set
When you apply a powerful deep learning algorithm to a simple machine learning problem
When you perform hyperparameter tuning and performance degrades

QUESTION 10

What kind of table compares classifications predicted by the model with the actual class labels?

Chaos table
Confusion matrix
Prediction plot
Residual plot