Building Classification Models with scikit-learn

Description

In this course,

First, you will learn what classification seeks to achieve, and how to evaluate classifiers using accuracy, precision, recall, and ROC curves.

Next, you will discover how to implement various classification techniques such as logistic regression, and Naive Bayes classification. You will then understand other more advanced forms of classification, including those using Support Vector Machines, Decision Trees and Stochastic Gradient Descent.

Finally, you will round out the course by understanding the hyperparameters that these various classification models possess, and how these can be optimized.