Machine Learning Beginner Set - 3

You create a simple report for a national fast-food chain organization which shows trend: Customers who visit the store more often and buy smaller meals spend more than customers who visit less frequently and buy larger meals. What is the most likely diagram that you can create?

• multiclass classification diagram

• linear regression diagram

• pivot table

• K-means cluster diagram

A organization that sells a spam filtering service to large companies wants to use machine learning. They currently have a list of 10000 keywords for spam detection. If a message contains more than few of these keywords, then it is identified as spam. What would be one advantage to use machine learning?

• It would look for new patterns in spam messages.

• It could go through the keyword list much more quickly.

• It could have a much longer keyword list.

• It could find spam messages using far fewer keywords.

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

• data cluster

• Supervised set

• population

• test data

You created a model to predict whether existing automotive insurance customers are more likely to buy homeowners insurance, and the model had a low variance but high bias. What does that say about the model?

• model is consistently wrong.

• model is inconsistently wrong.

• model is consistently right.

• model is equally right and wrong.

You work for an insurance company. Which machine learning project would add the most value for the company!

• Create an artificial neural network that would host the company directory.

• Use machine learning to better predict risk.

• Create an algorithm that consolidates all of your Excel spreadsheets into one data lake.

• Use machine learning and big data to research salary requirements.

What is one reason not to use the same data for both your training set and your testing set?

• data will underfit the model.

• data will choose wrong algorithm.

• not have enough data for both.

• data will overfit the model.

To build an internal email text prediction model to speed up the time that employees spend writing emails. What should you do?

• email data from all employees.

• email data from new employees.

• email data from seasoned employees.

• email data from employees who write the majority of internal emails.

A credit card processing company created a machine learning system that groups together customers who made similar purchases, and divides those customers based on customer loyalty. How would you describe this machine learning approach?

• unsupervised learning

• semi-supervised learning

• supervised learning

• reinforcement learning

A security company is thinking about adding machine learning algorithms to their computer network threat detection appliance. What is one advantage of using machine learning?

• protect against undiscovered threats.

• lower the hardware requirements.

• shorten development time.

• increase the speed of the appliance.

Your university wants to use machine learning algorithms to help sort through incoming student applications. An administrator asks if the admissions decisions might be biased against any particular group, such as women. What would be the best answer?

• Machine learning algorithms are based on math and statistics, and so by definition will be unbiased.

• There is no way to identify bias in the data.

• Machine learning algorithms are powerful enough to eliminate bias from the data.

• All human-created data is biased, and data scientists need to account for that.