Hi all,

I will try to be as concise as possible, but here is some background. The subject of my master thesis is ‘dutch named entity recognition using BERT’. This means that I will have to do entity extraction on dutch clinical notes, using google’s BERT model. The problem I have is that I’ve only taken two university programming courses (in python) and because the field of NLP is literally booming, I have a difficult time sketching out a strategic plan towards implementing this model successfully. The following is a list of things I consider doing, and I have no idea which of these are relevant here, or which important things I am potentially missing out on that would be necessary…

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1. Studying the book ‘Hands-On Machine Learning with Scikit-Learn and TensorFlow’ by Aurélien Géron
2. Following 3 to 4 introductory courses on NLP, TensorFlow, Machine Learning on Datacamp (online learning platform)
3. Following the Stanford CS224N: NLP with Deep Learning course
4. Familiarizing myself with Github, trying to implement and play around with the open-source models.
5. Reading blog posts on NLP
6. Reading papers on NLP
7. …?

Feel free to add to this list, or to provide comments on some of the listed elements!

FYI: I have a bachelor in Math (so I don’t expect any difficulties regarding the theoretics of ML)

My current professor doesn’t seem to show great interest in guiding me, so I have to refer to you guys! I would really greatly appreciate your input as I am a little bit lost at the moment to be honest.

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Thanks!