The objective of this post is to list down some of the pointers to keep in mind while building a Machine Learning model. Always start with the simplest of models. You can increase the complexity if the performance of a simple model is inadequate. Understand your dataset first. Build a baseline model before building any prediction model. I will expand on this further in another post. Complex models tend to over fit and simpler models tend to under fit. It is your job to find a balance betwee...
