Fine-grained Sentiment Analysis in Python (Part 1)

"Learning to choose is hard. Learning to choose well is harder. And learning to choose well in a world of unlimited possibilities is harder still, perhaps too hard." When starting a new NLP sentiment analysis project, it can be quite an overwhelming task to narrow down on a select methodology for a given application. Do we use a rule-based model, or do we train a model on our own data? Should we train a neural network, or will a simple linear model meet our requirements?