How to detect outliers | Data Science Interview Questions and Answers

Detect outliers using supervised, unsupervised, time series, and deep learning models

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In this tutorial, we will talk about how to answer the data science interview question about outlier detection. The tutorial covers the general strategies of answering the question, and provides example questions and answers.

Resources for this post:

• Video tutorial for this post on YouTube
• More video tutorials on anomaly detection and data science interview
• More blog posts on anomaly detection and data science interview

Strategies

The strategy for the outlier detection question is divide and conquer. We divide the answer into four parts:

• Outlier detection using the statistical definition of outliers
• Outlier detection using a supervised model
• Outlier detection using an unsupervised model
• Time series outlier detection

There is a bonus at the end to bring your answer to the next level.

The answer for each part includes three components. They are:

• When to use the method?