In this chapter, we introduced matrices through the core.matrix and clatrix libraries. The following are the points that we covered:
- We've discussed how to represent, print, and fetch information from matrices through core.matrix and clatrix. We've also discussed how we can generate matrices with some random data.
- We've talked about some of the rudimentary operations on matrices, such as equality, addition, multiplication, transpose, and inverse.
- We've also introduced the versatile Incanter library that is used to visualize plots and charts of data, through an example on using matrices.
Next, we will study some basic techniques for prediction using linear regression. As we will see, some of these techniques, in fact, are based on simple matrix operations. Linear regression is actually a type of supervised learning, which we will discuss in the next chapter.
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