That being said, when it comes to the volume of practical applications that come up for the many teams that we work with, the vast majority can be solved by the techniques outlined in the post. These techniques are simpler, but often overlooked. We believe that they should often be a starting point, and most of the time they end up being good enough for the job.
I'd agree - and also, it should be made clear that a Twitter classifier with 80% accuracy is probably a long way from something that you would apply to the actual Twitter firehose.
But the article is a very nice introduction to text mining (alas, not NLP)!
Author here, happy to answer questions and share our vision of it. Many problems require more complex approaches, and we definitely have Fellows tackle some of those (https://blog.insightdatascience.com/entity2vec-dad368c5b830).
That being said, when it comes to the volume of practical applications that come up for the many teams that we work with, the vast majority can be solved by the techniques outlined in the post. These techniques are simpler, but often overlooked. We believe that they should often be a starting point, and most of the time they end up being good enough for the job.