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Data Science and Machine Learning (Theory and Projects) A to Z - Feature Engineering: Categorical Features

Data Science and Machine Learning (Theory and Projects) A to Z - Feature Engineering: Categorical Features

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

Created by

Wayground Content

FREE Resource

The video tutorial focuses on feature engineering, particularly preparing datasets for machine learning algorithms. It discusses the challenges of handling data inconsistencies and converting categorical features into numeric form. The tutorial introduces one-hot encoding as a method to improve model performance by expanding categorical features into binary vectors. An example from the Python Data Science Handbook is used to illustrate these concepts.

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OPEN ENDED QUESTION

3 mins • 1 pt

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