I think this is a good idea for a series. Although I think more detail needs to be given on the actual path, that is after all the purpose of the series. Most of this article seemed to be describing what NLP is and why it's hard. This isn't bad and some attention should be given to it but people looking to find the path into NLP will already be familiar with most of this information. I was expecting a bit more of a syllabus type format. There was mention of needing some college level algebra and statics, I would have liked more detail in this area with links to more resources (classes, articles, datasets, etc). Keep up the good work!
Agreed on more substantive detail needed. I was surprised at the lack of mention of many of the basic techniques and domains that a person interested in should consider learning about.
The following are all germane but not mentioned: text analysis/mining, controlled vocabularies, indexing, taxonomies, ontology, semantic web, latent semantic analysis, latent dirichlet allocation, corpus analysis, document similarity analysis, tf-idf, ngrams, and skip grams just to mention a few.
In general the article is a good idea but their needs to be more of a description of the domain landscape and then "paths" plotted through that landscape that lead to interesting and useful competency.
That's a great point. I wonder if there would be a better way to introduce meaningful, actionable topics of study to an introductory-level audience of people who may have never heard of NLP.
