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WorksheetsAAS 02 - Anomaly Detection
Total questions: 15
Worksheet time: 10mins
This picture shows an application of ...
Supervised Learning: Classification
Unsupervised Learning: Clustering
Unsupervised Learning: Prediction
Supervised Learning: Regression
__________________ algorithms enable the computers to learn from data, and even improve themselves, without being explicitly programmed.
Artificial Intelligence
Machine Learning
Deep Learning
Traditional Learning
What are the three types of Machine Learning? Choose three.
Supervised Learning
Learning Differentiated
Unsupervised Learning
Reinforcement Learning
Technical Learning
What are the two types of Unsupervised Learning?
Loitering
Clustering
Blind Signal Separation
Dissociation
In this type of Machine Learning, an AI system is presented with unlabeled, uncategorized data and the system’s algorithms act on the data without prior training. The output is dependent upon the coded algorithms.
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Technique Learning
TF-IDF penalizes heavily words that occur very frequently across multiple documents – true or false
True
False
Which of the following cannot be used for time-series forecasting?
Temporal Convolutional Network
Multivariate regressor
Recurrent Neural Network
Autoencoder Neural Network
An Intrusion Detection System (IDS) .....
can be configured to allow the intruder IP when an alert is generated
opening the network connection for an active and passive attack
inspects network activities and identifies suspicious patterns that may indicate a network attack
an identifier for the correct usage of particular computer or total network
Goals of IDS
Mobility and allow for a stable connection
Take action and allowing an attack to the network
Identify abnormal behaviour of network or misuse of resources
Different ways to transmit data securely and safely
Select the correct option.
A. Supervised learning methods include autoencoders.
B. The output and input of the autoencoder are identical.
Both the statements are TRUE.
Statement A is TRUE, but statement B is FALSE.
Statement A is FALSE, but statement B is TRUE.
Both the statements are FALSE.
Autoencoders are trained without supervision.
True
False
Cannot be predicted
may be
______________ is a recommended model for pattern recognition in unlabelled data
CNN
RNN
Autoencoders
Shallow neural networks
Autoencoders cannot be used for Dimensionality Reduction.
True
False
May be
Cannot say
Select the true statements
we can use clustering algorithms to discover implicit grouping within the data
Autoencoders is a supervised learning algorithm
k-means is Density-based clustering
The goal of clustering a set of data is to
divide them into groups of data that are near each other
choose the best data from the set
determine the nearest neighbors of each of the data
predict the class of data
