Data Preprocessing for Machine Learning
A guide to effectively preprocess data for machine learning models.
11 month ago
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CONTEXT
Data preprocessing is a crucial step in machine learning to ensure that data is in the right format and quality for model training.
OBJECTIVE
To outline the essential steps and techniques for preprocessing data.
FORMAT
This guide will cover steps such as data cleaning, normalization, encoding categorical variables, and handling missing values.
EXAMPLES
1. Removing duplicates from a dataset. 2. Normalizing data using Min-Max scaling. 3. One-hot encoding categorical variables.
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