Hey all! Just wanted to share something cool that's been on my mind lately. So you know how building a complex neural network can feel like solving some crazy math puzzle? Well, it turns out there’s this simple equation called y=ax+b - the straight line one - which helps us understand changes in output based off of input shifts! Crazy right?! Instead of diving deep in those complex layers and nodes (which can be a real brain bender), we use good ol' fashioned algebra to get our heads wrapped around it. Makes me wonder, what other simple concepts could help us understand more complicated stuff? Hope you find this as interesting as I did! Let’s keep learning together :)
Source:
https://www.freecodecamp.org/news/neural-networks-explained-using-y-ax-b/