EDA and analyzing the distribution of data
Analyzing the Distribution of Your Data for Effective Data Analysis
Thank you for all your kind words about my ChatGPT article (and other AI writeups).
Just wanted to share something that would be interesting to y’all.
LinkedIn invited me to contribute to their advice pieces geared at helping developers and other tech people get better.
This is obviously a huge W for this cult, and I’m excited to see the opportunities it presents. As I looked through some articles they had asked me to contribute to, one stood out How do you apply data transformations to improve model performance in EDA? (go engage with the article if you’d like to support me). However, the character limit for contributions was too little so I thought I’d do a more fleshed-out piece. You can find a more detailed write-up below. In it, I discuss why analyzing the distribution of your data is important, the common techniques to do so, and some common mistakes people make. If that is interesting to you, give it a read.
I appreciate all the love you’ve shown me. Much more to come. Catch you soon.
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