Summary
In this chapter, we continued working on the online advertising click-through prediction project. This time, we overcame the categorical feature challenge by means of the one-hot encoding technique. We then resorted to a new classification algorithm, logistic regression, for its high scalability to large datasets. The in-depth discussion of the logistic regression algorithm started with the introduction of the logistic function, which led to the mechanics of the algorithm itself. This was followed by how to train a logistic regression model using gradient descent.
After implementing a logistic regression classifier by hand and testing it on our click-through dataset, you learned how to train the logistic regression model in a more advanced manner, using SGD, and we adjusted our algorithm accordingly. We also practiced how to use the SGD-based logistic regression classifier from scikit-learn and applied it to our project.
We then continued to tackle problems we might...
