Let's introduce yourself to Unsupervised learning, which is a type of machine learning problem where the training data consists of a set of input vectors but no corresponding target values
All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.
All our activities include solutions with explanations on how they work and why we chose them.
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True or False: Clustering is a common task in unsupervised learning, where data points are grouped together based on similarity
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Imagine you work for an e-commerce company. The company has a large database of customer transactions, and your task is to segment customers into different groups for targeted marketing. Which unsupervised learning technique would you use?
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You are a financial analyst at a bank and need to detect potentially fraudulent transactions in a credit card dataset. How could unsupervised learning be applied to identify unusual transaction patterns indicative of fraud?
