missing data – Machine Learning Interviews

Name a few problems that data analysts typically encounter?

Posted on June 28, 2019June 28, 2019 by MLInterview

Some of the problems encountered by a data analyst are : Biased Data : Data could be biased due to the source from which it is collected. For instance, suppose you collect data to determine the winner of an electoral campaign, collecting from a specific region alone introduces one form of a bias, while collecting…

How do you handle missing data in an ML algorithm ?

Posted on March 1, 2019September 4, 2019 by MLInterview

Missing data is caused either due to issues in data collection or sometimes, the data model could allow for missing data (for instance, the field ‘maximum credit limit on any of your cards’ might not make sense for someone who has no credit cards…). With missing data, typically the ML algorithm implementation might fail with…