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LinkedIn Machine Learning

Exam Type: LinkedIn Skill Test
Last Update February, 2024

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Exam Detail

Machine Learning linkedin assessment

You work for an organization that sells a spam filtering service to large companies. Your organization wants to transition its product to use machine learning. It currently a list Of 250,00 keywords. If a message contains more than few of these keywords, then it is identified as spam. What would be one advantage of transitioning to machine learning?

  •  The product would look for new patterns in spam messages.
  •  The product could go through the keyword list much more quickly.
  •  The product could have a much longer keyword list.
  •  The product could find spam messages using far fewer keywords.

Machine Learning skill assessment linkedin

You work for a music streaming service and want to use supervised machine learning to classify music into different genres. Your service has collected thousands of songs in each genre, and you used this as your training data. Now you pull out a small random subset of all the songs in your service. What is this subset called?

  •  data cluster
  •  Supervised set
  •  big data
  •  test data

Machine Learning linkedin quiz

In traditional computer programming, you input commands. What do you input with machine learning?

  •  patterns
  •  programs
  •  rules
  •  data

Machine Learning linkedin test

Your company wants to predict whether existing automotive insurance customers are more likely to buy homeowners insurance. It created a model to better predict the best customers contact about homeowners insurance, and the model had a low variance but high bias. What does that say about the data model?

  •  It was consistently wrong.
  •  It was inconsistently wrong.
  •  It was consistently right.
  •  It was equally right end wrong.

Machine Learning linkedin assessment questions

You want to identify global weather patterns that may have been affected by climate change. To do so, you want to use machine learning algorithms to find patterns that would otherwise be imperceptible to a human meteorologist. What is the place to start?

 

  •  Find labeled data of sunny days so that the machine will learn to identify bad weather.
  •  Use unsupervised learning have the machine look for anomalies in a massive weather database.
  •  Create a training set of unusual patterns and ask the machine learning algorithms to classify them.
  •  Create a training set of normal weather and have the machine look for similar patterns.

linkedin Machine Learning assessment

linkedin Machine Learning test

Machine Learning linkedin background

 

 

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