January 2025
Intermediate to advanced
614 pages
15h 37m
English
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3.1 Data Cleaning and Handling Missing Data
Data cleaning is a crucial step in the data preprocessing pipeline, involving the systematic identification and rectification of issues within datasets. This process encompasses a wide range of activities, including:
Detecting corrupt data
This crucial step involves a comprehensive and meticulous examination of the dataset to identify any data points that have been compromised or altered during various stages of the data lifecycle. This includes, but is not limited to, the collection phase, where errors might occur due to faulty sensors or human input mistakes; the transmission phase, where data corruption can happen due to network issues or interference; and the storage phase, where data might be corrupted ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.