What is it called when a human trains a model to learn with examples?
Machine Learning Quiz

Quiz
•
Computers
•
9th - 12th Grade
•
Easy
KENNETH GUNTHER
Used 2+ times
FREE Resource
19 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Unsupervised Learning
Supervised Learning
Training
Labeling
Answer explanation
When a human trains a model using labeled examples, it is called Supervised Learning. This method involves providing the model with input-output pairs to learn from, enabling it to make predictions on new data.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a computer program designed to make a decision called?
Model
Feature
Label
Training
Answer explanation
A computer program designed to make a decision is called a 'Model'. In machine learning, a model is trained on data to make predictions or decisions based on input, distinguishing it from features, labels, or training processes.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the process of giving examples to a model so it can learn called?
Labeling
Unsupervised Learning
Training
Modeling
Answer explanation
The process of giving examples to a model so it can learn is called Training. During training, the model adjusts its parameters based on the provided examples to improve its performance on tasks.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is finding patterns in data that doesn't have any labels called?
Supervised Learning
Unsupervised Learning
Training
Labeling
Answer explanation
Finding patterns in unlabeled data is known as Unsupervised Learning. Unlike Supervised Learning, which uses labeled data, Unsupervised Learning identifies hidden structures without predefined categories.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In _________ model keeps on increasing its performance using a Reward Feedback to learn the behavior or pattern
clustering
reinforcement learning
semi supervised
reinforcement
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is Reinforcement learning?
All data is unlabelled and the algorithms learn to inherent structure from the input data
All data is labelled and the algorithms learn to predict the output from the input data
It is a framework for learning where an agent interacts with an environment and receivesa reward for each interaction
Some data is labelled but most of it is unlabelled and a mixture of supervised andunsupervised techniques can be used.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What are different types of machine learning?
Supervised, Unsupervised, and Reinforcement
Automatic, Manual, and Hybrid
Cognitive, Behavioral, and Analytical
Static, Dynamic, and Interactive
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