ML Check

• Which the following examples, would you address using an unsupervised learning algorithm? (Check all that apply.)

• • Predicting email as spam/not spam.

• • Grouping a set of news articles.

• • Segmenting customers based on their recency, frequency and monetary analysis

• • Diagnosing patients as diabetic or not.

What model can used for predicting sales volume of a smartphone?

• Classification

• Clustering

• Regression

• RFM analysis

Which model will you employ to predict whether your customers will churn or not?

• Regression

• Classification

• Clustering

• Gradient Descent

• Data set is given.

• We know the correct data should look like.

• Relationship b/w input and output is known.

What type of learning is summarized above?

• Supervised Learning

• Unsupervised Learning

• I need to learn more to answer this

• Semi Supervised Learning

• Little or no idea about the output

• Derive structures from data and we don’t know the effect of variables

• Derive structure by clustering data based on relationship b/w variables

• No feedback based on the results

What type of learning is summarized above?

• Reinforcement Learning

• Active Learning

• I am yet to learn

• Unsupervised Learning