COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Unsupervised Learning:Clustering
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Supervised Learning:Classification
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Reinforcement Learning
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Unsupervised Learning:Regression
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Detailed explanation-1: -Supervised learning techniques are widely employed in credit card fraud detection, as they make use of the assumption that fraudulent patterns can be learned from an analysis of past transactions.
Detailed explanation-2: -Fraud Detection Using Machine Learning deploys a machine learning (ML) model and an example dataset of credit card transactions to train the model to recognize fraud patterns. The model is self-learning which enables it to adapt to new, unknown fraud patterns.
Detailed explanation-3: -In Machine Learning, problems like fraud detection are usually framed as classification problems-predicting a discrete class label output given a data observation. Examples of classification problems that can be thought of are Spam Detectors, Recommender Systems and Loan Default Prediction.
Detailed explanation-4: -All images except one image were correctly clustered. This indicates that we can perform image classification using an unsupervised learning approach with transfer learning.