Category: Machine Learning for Hackers

In the final chapter the authors introduce Support Vector Machines (SVM). What SVM do are generalize linear decision boundaries for… Read more

Are you a heavy Twitter user? Would you like to build a custom recommendation system in R that will recommend… Read more

k-nearest neighbors (kNN) is the topic of chapter 10. The authors say it’s the most intuitive of the machine learning… Read more

In this chapter we learn a little about Multidimensional Scaling, or MDS for short. Like PCA in Chapter 8, MDS… Read more

This is a tidy chapter on principle component analysis (PCA). There are many fine tutorials on PCA to be found… Read more

The title of this chapter, “Optimization: Breaking Codes”, sounds more exciting than it really is. The code breaking is attempted… Read more

Chapter 6 covers orthogonal polynomial regression, cross-validation, regularization and a touch of logistic regression. The case study is predicting popularity… Read more

This chapter covers linear regression. The case study is predicting page views for web sites given unique visitors, whether the… Read more

This chapter explains how to create a ranking algorithm to prioritize email messages in your inbox. The authors mention Google… Read more

In this chapter you build a naïve Bayes classifier to classify an email as spam or not spam (or “ham”… Read more