Tired of spending “too much time” doing data exploration before training your Machine Learning models?
Looking for a faster way to understand data issues and patterns, before you dive into the fun part of training your ML model?
Wanna learn how to train better ML models, by finding and fixing issues in your data?
In this repo you can find a short Python script that used the Sweetviz library to do data exploration at the speed of light.
I also invite you to read the original article I published on my site:
📝 Fast And Easy Data Exploration For Machine Learning
You need Python >= 3.7 and
$ pip install sweetviz
I attached a sample dataset for a churn prediction model, that you can quickly explore with a one-liner.
$ python eda.py --file v1.csv --target Churn
If you want to learn more about real-world ML topics and become a better data scientist
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