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WorksheetsMachine learning
Total questions: 20
Worksheet time: 11mins
What are the three types of Machine Learning? Choose three.
Supervised Learning
Learning Differentiated
Unsupervised Learning
Reinforcement Learning
Technical Learning
__________________ algorithms enable the computers to learn from data, and even improve themselves, without being explicitly programmed.
Artificial Intelligence
Machine Learning
Deep Learning
Traditional Learning
This picture shows a result of ...
Supervised Learning: Classification
Unsupervised Learning: Regression
Unsupervised Learning: Prediction
Supervised Learning: Regression
Fraud Detection, Image Classification, Diagnostic, and Customer Retention are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
What is the primary difference between supervised and unsupervised learning?
(a) Supervised learning focuses on text data, while unsupervised learning focuses on numerical data.
(b) Supervised learning uses labeled data, while unsupervised learning uses unlabeled data.
(c) Supervised learning predicts continuous values, while unsupervised learning predicts discrete values.
(d) Supervised learning is more accurate than unsupervised learning.
Real-Time decisions, Game AI, Learning Tasks, Skill Aquisition, and Robot Navigation are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
Which of the following is not type of learning?
Semi-unsupervised Learning
Unsupervised Learning
Supervised Learning
Reinforcement Learning
What kind of learning algorithm for "Future stock prices or currency exchange rates"?
Recognizing Anomalies
Prediction
Generating Patterns
Recognition Patterns
What is Machine Learning? (Choose 3 Answers)
Artificial Intelligence
Machine Learning
Data Statistics
Deep Learning
Which among the following is not true for a Bayesian classifier?
A (natural) class is to predict the values of features for members of that class.
It is a probabilistic model.
It is based on Bayes' theorem.
It is not used in data mining.
In Gaussian mixture model clustering, the number of Gaussian distribution functions used is equal to
Number of clusters
Number of attributes
Number of instances
Number of iterations
Is Gaussian mixture model Probabilistic?
Yes, It is probabilistic.
No, it is not probabilistic.
Is k-mean clustering supervised?
Yes, It is supervised
No, it is unsupervised.
Is Gaussian mixture model supervised?
Yes, It is supervised
No, it is unsupervised.
Does k-mean algorithm always converge?
Yes
No
Which clustering method takes care of oblong dataset?
k-mean
Gaussian mixture model
Decision tree
All of the answers
Which clustering method takes care of variance in data?
k-mean
Gaussian mixture model
Decision tree
All of the answers
Can Decision Tree be used for clustering?
Yes
No
In k-mean algorithm, K stands for
Number of data
Number of clusters
Number of attributes
Number of iterations
What are the two types of Unsupervised Learning?
Loitering
Clustering
Association
Dissociation
