Part 2 Intermediate level

Think of the journey in this book as your workshop, where raw concepts and fundamentals are turned into case studies and working solutions using Python. Each concept we cover, each algorithm we study, and each case study we solve here is a building block, but it’s up to you to put them together in creative ways and implement them in your real-life business. This implementation should help you solve business problems in ways that are both logical and creative. The algorithms, tools, and techniques you are learning will allow you to create functional, powerful solutions—step by step.

The true art of machine learning lies not in knowing all the algorithms by heart or cramming the deepest of mathematical concepts but in knowing how to approach the problem, use the available dataset effectively and efficiently, and finally solve problems. You should not ignore the user experience while revealing the insights to the end user.

You’ve learned the fundamentals of unsupervised learning in the first part; it is now time to move to slightly more advanced topics. In this part, we’ll dive into association rules, advanced clustering, and dimensionality reduction techniques.