Today I'm going to suggest a great resource for those interested in getting into Natural Language Processing. While not new or recent, I cant say it's outdated either: it's labeled: August 2016.
Matt Kiser, from Algorithmia, posted this lengthy blog: Everything you Need to Know about Natural Language Processing.
NLP is a cross-disciplinary field that uses concepts of artificial intelligence, computer science, and computational linguistics. As per Kiser:
"NLP is a way for computers to analyze, understand, and derive meaning from human language in a smart and useful way. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation." [source]
So, in Matt's post, you'll learn about:
- uses of NLP algorithms
- open source NLP libraries
- examples of NLP use cases
- recommended NLP books for beginners
- recommended NLP videos, tutorials, and more.
I personally haven't gotten much into NLP yet, though I have to say that I played, hands-on, with a few machine learning tutorials for NLP. While I'm currently more into generalized ML and DL, it is very likely that I'll get into NLP at a later time. Anyhow, if you decide you want to embark on a self-learning NLP track, Matt's post might be a good start:
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Cristi Vlad Self-Experimenter and Author