This chapter provides an overview of machine learning (ML) techniques for doing data analysis. In the previous chapters, we have explored some of the techniques that can be used by human beings to analyze and understand data. In this chapter, we look at how ML techniques could be used for similar purposes.
At the heart of ML is a number of algorithms that have proven to work for solving specific categories of problems with a high degree of effectiveness. This chapter covers the following popular ML methods:
- Decision trees
- Random forests
- Ridge and lasso regression
- k-means cluster analysis
It also covers the role of natural language processing (NLP) in effectively analyzing certain types of data problems. The discussion in this chapter is limited to traditional machine learning methods. It does not cover newer methods such as deep...
