Simplify Data Preprocessing with Python's Column Transformer: A Step-by-Step Guide

In this comprehensive YouTube video, we dive into the powerful world of feature transformation using the Column Transformer in Python's machine learning ecosystem. Whether you're a beginner or an experienced practitioner, understanding how to preprocess and transform features is crucial for building robust ML models.

Whether you're working on classification, regression, or any other machine learning task, mastering the art of feature transformation through the Column Transformer can significantly elevate your model's efficiency

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As a full-time data analyst/scientist at a fintech company specializing in combating fraud within underwriting and risk, I've transitioned from my background in Electrical Engineering to pursue my true passion: data. In this dynamic field, I've discovered a profound interest in leveraging data analytics to address complex challenges in the financial sector.

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[RyanAndMattDataScience]

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[henry-oi]

Great video. Feel like this is an important concept and you explain it in 15 mins. Thanks. I do have a few question. 1) if i want to use the odc like u explain in another video, do i clarify another transformer (enc) for example:
sizes =['Small', 'Medium', 'Large']
enc
ct = make_column_transformer (
(ohe, ['city']),
(enc, ['size']),
remainder = 'passthrough'
)

[henry-oi]

Also, you give us a simple data set, which is great. However, I had the trouble when i have a large data set and have a lot of columns, and i don't know how to retrieve the column name after column transform. Will you explain how to do it in later projects/videos? Again, thanks for all the great work. Having a blast following through the playlist.

[andyhong]

Like your others, there are lots of good stuffs in a concise video. Wonder if you could make the Jupiter notebook available for this video or future's.

[chintan]

The keyboard is very loud, may be keep it away from mic.