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Data Preprocessing For Machine Learning

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Overview

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This course covers essential data preprocessing techniques such as handling missing values, encoding categorical features, feature scaling, and splitting the dataset for training and testing.

Syllabus

Lesson 1: Handling Missing Values
Lesson 2: Encoding Categorical Features
Lesson 3: Feature Scaling
Lesson 4: Train-Test Split
Lesson 5: Building Full Preprocessing Pipeline for the Titanic Dataset

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