well, I'm going to take something out of my chest. every time I shared a project here using machine learning people always gave me crap. saying my models were simplistic, or I did something wrong or the solution didn't work 100% of the time. well, I studied ML back in college. the basics, the algorithms that started all, linear regression, perceptron, adaline, knn, kmeans... and guess what? ML doesn't work 100% of the time. I always wanted to see how people would react when a car driven by ml hits something or when they based an important decision based on the classification of an nn. ML should be used along side human intelligence not by itself. you don't blindly trusts a black box.