How to detect outliers | Data Science Interview Questions and Answers | Machine Learning

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.

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

⏰ Timecodes ⏰
0:00 - Intro
0:19 - Strategies
0:57 - Question: How to detect outliers?
2:10 - Follow-up Question 1: How to use IQR to detect outliers?
2:42 - Follow-up Question 2: How to use a supervised model to detect outliers?
3:50 - Follow-up Question 3: How to use an unsupervised model to detect outliers?
4:45 - Follow-up Question 4: How to use a time series model to detect outliers?
5:28 - Bonus Answer: Use Autoencoder for Anomaly Detection

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