NeuroData Training : Quiz2
NeuroData Training: Machine Learning Fundamentals Quiz
Test your knowledge of machine learning concepts and applications with our engaging quiz! Perfect for students, professionals, and anyone interested in understanding the intricacies of machine learning.
- 10 multiple-choice questions
- Immediate feedback on your answers
- Enhance your understanding of AI and data science
What is an example of a commercial application for a machine learning system?
Data entry system.
A data warehouse system.
A product recommendation system.
A massive data repository.
Why is naive Bayes called naive?
It naively assumes that you will have no data.
It does not even try to create accurate predictions.
It naively assumes that the predictors are independent from one another.
It naively assumes that all the predictors depend on one another.
What is one reason not to use the same data for both your training set and your testing set?
You will almost certainly underfit the model.
You might not have enough data for both.
You will pick the wrong algorithm.
You will almost certainly overfit the model.
How is machine learning related to artificial intelligence?
Artificial intelligence focuses on classification, while machine learning is about clustering data.
Machine learning is a type of artificial intelligence that relies on learning through data.
Artificial intelligence is form of unsupervised machine learning.
Machine learning and artificial intelligence are the same thing.
What is Stacking ?
You stack your training set and testing set together.
You use several machine learning algorithms to boost your results.
You use different versions of machine learning algorithms.
The predictions of one model become the inputs another.
What is a scatter plot?
A graph that shows the relationship of two data sets.
A graph drawn using rectangular bars to show how large each value is.
A graph that shows data changing over time.
A graph that shows information that is connected in some way.
You created machine learning system that interacts with its environment and responds to errors and rewards. What type of machine learning system is it?
Semi-supervised learning
Supervised learning
Unsupervised learning.
Reinforcement Learning
Your data science team must build a binary classifier, and the number one criterion is the fastest possible scoring at deployment. It may even be deployed in real time. Which technique will produce a model that will likely be fastest for the deployment team use to new cases?
Logistic regression
Random forest
KNN
Deep neural network
Which of the following is NOT supervised learning?
Decision Tree
Linear Regression
PCA
Naive Bayesian
Suppose we would like to perform clustering on spatial data such as the geometrical locations of houses. We wish to produce clusters of many different sizes and shapes. Which of the following methods is the most appropriate?
Decision Trees
Density-based clustering
K-mean clustering
Model-based clustering
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