This little reference guide is something I’ve been putting together mainly for myself. It's still a work in progress, but It’s a collection of data science topics that I often find myself revisiting to refresh my memory and gain a deeper understanding.

From foundational concepts like distance metrics and cost functions to more advanced techniques like clustering, classification, and neural networks, I’ve organized everything in a way that helps me understand and apply these methods better. It’s not an exhaustive textbook, but more of a handy resource to quickly revisit the essentials whenever I need to. Hopefully, others working in data science might find it just as useful!