March 2024
Intermediate to advanced
814 pages
22h 10m
English
Content preview from Extending Power BI with Python and R - Second Edition
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19
Exploratory Data Analysis
In Chapter 17, we discussed the challenges of using machine learning without premium or embedded capacity. One of the key pitfalls we highlighted was blindly applying automated machine learning (AutoML) solutions to a dataset, which often results in inaccurate models. To overcome this limitation, a critical step is to gain a deep understanding of the inherent characteristics of the dataset.
To accomplish this, this chapter introduces the concept of exploratory data analysis (EDA). This approach to analysis, pioneered by John Tukey, encourages statisticians to thoroughly explore the data and formulate hypotheses. By doing so, we can extract valuable information that ultimately enhances our understanding of the dataset ...
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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.