6 Dimensionality reduction (advanced)
“Life is really simple, but we insist on making it complicated - Confucius”
Simplicity is a virtue. Both in life and in data science. We have discussed a lot of algorithms so far – a few of them are simple enough and some of them are a bit complicated. In Part one of the book, we studied simpler clustering algorithms and in the last chapter, we examined advanced clustering algorithms. Similarly, we studied a few dimensionality algorithms like PCA in chapter 3. Continuing on the same note, we will study two advanced dimensionality reduction techniques in this chapter.
The advanced topics we are covering this part and the next part of the book are meant to prepare you for complex problems. Whilst you can apply these advanced solutions, it is always advisable to start with the classical solution like PCA for dimensionality reduction. And if the solution achieved it not at par, then you can try the advanced solutions.