Скачать или смотреть (ML/AI) End-to-End Data Preprocessing Part-1

Master the most important step of any machine learning workflow — data preprocessing.
In this practical, beginner-friendly tutorial, we walk through a complete codelab where you’ll learn:

Codelab link - https://colab.research.google.com/dri...

🔹 Fixing Missing Values

How to identify missing data

When to use mean vs median vs most frequent imputation

Why blindly removing rows is usually a bad idea

Using SimpleImputer, KNNImputer, and custom strategies

🔹 Handling Categorical Data

Understanding nominal vs ordinal categories

When to use Label Encoding, One-Hot Encoding, and Ordinal Encoding

Common mistakes to avoid (like leaking target information)

Encoding inside an sklearn Pipeline the correct way

🔹 Full Hands-On Codelab

We build the preprocessing workflow step-by-step:

Loading a real dataset

Fixing missing values

Encoding categories

Combining numerical + categorical transformations

Training a model using the clean data

This video is perfect for:
✔️ Machine learning beginners
✔️ Students preparing for interviews
✔️ Engineers who want to understand preprocessing deeply
✔️ Anyone building ML models in Python



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