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This book is golden! (and I think I'll have to read it again because it's so full of information!)
For anyone trying to understand their models, Serg Masís' book "Interpretable Machine Learning with #Python" provides the right mix of theory and practical approaches. It has both a high-level and applied perspective, which I really enjoyed, and gives both practitioners and those new to the field a
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Going back to interactive #EDA with few-liners, we have
📦 SweetViz (by Francois Bertrand)
This one gives you a really nice (and clean) overview of your data. You have different tabs that unfold and show you what's in your data. Here's the GIF that shows the report: https://cosimameyer.com/images/single-blog/sweet_viz_penguins.gif
🔗 https://pypi.org/project/sweetviz/
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One more one-line approach is provided by
📦 DTale (by AhlDev and Andrew Schonfeld)
Unlike the other one-line workflows in #Python’s #EDA, DTale takes a different approach: it shows you the tabular data as it is and allows you to gain an understanding of different aspects based on the tabular view. Here’s the demo video: https://cosimameyer.com/images/single-blog/dtale_penguins.gif
🔗 https://githu
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When looking at #EDA packages in #Python, you will find many few-line approaches that give you a nice standardized EDA output. One of them is
📦 AutoViz (by Hiron Roy and Ram Seshadri)
It’s built around one function that provides you with #HTML files to interactively explore your data. You can access the demo gif here: https://cosimameyer.com/images/single-blog/autoviz_penguins.gif
🔗 https://pypi
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This book is golden! (and I think I'll have to read it again because it's so full of information!)
For anyone trying to understand their models, Serg Masís' book "Interpretable Machine Learning with #Python" provides the right mix of theo…
And the last package on the list is another really nice solution to get a quick overview of your data:
📦 YData Profiling
A great solution for quickly gaining insights into your data. This tool provides variable-level insights, descriptive …
Going back to interactive #EDA with few-liners, we have
📦 SweetViz (by Francois Bertrand)
This one gives you a really nice (and clean) overview of your data. You have different tabs that unfold and show you what's in your data. Here's the …
The next library has also an equivalent in #rstats - it's called
📦 summarytools (by Chaoran L. and AJ)
It builds on the original idea of summarytools in #rstats and implements my favorite go-to feature: the dfSummary function.
🔗 https://…
The next one is again something I can't present without being biased because it's the #Python version of #overviewR (though still very much a work in progress).
📦 overviewpy
Like overviewR, this library has a clear focus on cross-sectional…
One more one-line approach is provided by
📦 DTale (by AhlDev and Andrew Schonfeld)
Unlike the other one-line workflows in #Python’s #EDA, DTale takes a different approach: it shows you the tabular data as it is and allows you to gain an u…
When looking at #EDA packages in #Python, you will find many few-line approaches that give you a nice standardized EDA output. One of them is
📦 AutoViz (by Hiron Roy and Ram Seshadri)
It’s built around one function that provides you with…
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