dirty-data-science/python
Tutorial material on machine learning with dirty data in Python
This tutorial helps you learn how to build effective machine learning models even when your data isn't perfect. It guides you through the process of taking real-world, messy datasets and transforming them into a clean, usable format for model training. This is for anyone who wants to apply machine learning but often encounters real-world data imperfections.
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Use this if you are a data scientist or analyst struggling to get good results from machine learning models because your input data is incomplete, inconsistent, or noisy.
Not ideal if you already have perfectly clean datasets and are looking for advanced model architecture or deployment strategies.
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61
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8
Language
Python
License
BSD-2-Clause
Category
Last pushed
Jul 07, 2024
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