Which ML Model To Use?
It is normal for a python developer , new to artificial intelligence, to get scared by several models and neural network structures, that are accessible and readily available. We frequently wrack our psyches and evaluate a lot of calculations to get the best model. My educator frequently used to express that the most ideal route is to evaluate every conceivable model until you make sense of the best one. After several years of hard work and implementing a lot of models later. Gradually I built up an instinctive comprehension of how various models fit themselves to the information. So here I am sharing my understanding of "Which machine learning model to use?" I have categorized machine learning models into different subgroups for better understanding. I will be explaining in brief about the models in each category and discussing their application. Group - 1 Linear statistical models: Generalized Linear Models : These models are based on probability distributions an