Machine learning is particularly good at digesting large amounts of data very quickly and identifying patterns or finding anomalies or outliers in that data.

Outlier Detection The z-score is used to identify outliers in a dataset. Any data point with a z-score greater than 3 or less than -3 is considered an outlier.

This article explains how to programmatically identify and deal with outlier data (it's a follow-up to "Data Prep for Machine Learning: Missing Data"). Suppose you have a data file of loan ...

In this overview, Leila Gharani explores how integrating Python into Excel redefines how you handle external data. From establishing live connections to datasets using Power Query to using Python ...

Discover how Python in Excel transforms data analysis with advanced features. Is it worth the hype? Find out if it’s right for your workflow.

The Data Science Lab Data Prep for Machine Learning: Outliers After previously detailing how to examine data files and how to identify and deal with missing data, Dr. James McCaffrey of Microsoft ...