Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Machine Learning Mode

The video explains the concept of linear models in machine learning, highlighting the difference between linear and affine functions. It discusses how a constant addition affects linearity and how such models are termed in machine learning literature. Despite mathematical definitions, affine models are often referred to as linear in machine learning, emphasizing the importance of understanding these terms when reading academic papers and codes.

What is the main difference between linear functions and affine functions as discussed in the text?

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Discuss the significance of the term 'affine model' in the context of machine learning.

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Explain why the model with an added constant is considered linear in machine learning literature.

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How does the addition of a constant affect the linearity of a function according to the text?

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What implications does the definition of linearity have for understanding machine learning models?

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