In this chapter you will learn the basics of applying logistic regression and support vector machines (SVMs) to classification problems. You'll use the scikit-learn library to fit classification models to real data.

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2

Loss functions

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In this chapter you will discover the conceptual framework behind logistic regression and SVMs. This will let you delve deeper into the inner workings of these models.

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3

Logistic regression

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In this chapter you will delve into the details of logistic regression. You'll learn all about regularization and how to interpret model output.

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4

Support Vector Machines

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In this chapter you will learn all about the details of support vector machines. You'll learn about tuning hyperparameters for these models and using kernels to fit non-linear decision boundaries.

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