Topics
Text embeddings
http://mccormickml.com/2016/04/19/word2vec-tutorial-the-skip-gram-model/
https://www.tensorflow.org/tutorials/text/word2vec
Deep learning (DL)
https://www.manning.com/books/deep-learning-with-python - This is one of the best sources for a very solid practical / developer centric overview of deep learning and it's various architectures written by the creator of the Keras library. Less "mathy" and more focused on underlying processes.
Ultimate tool box reference(s)
Simple API in Python overview - https://towardsdatascience.com/deploy-apis-with-python-and-docker-4ec5e7986224
Feature extraction
Straight forward and useful. https://towardsdatascience.com/feature-selection-and-eda-in-python-c6c4eb1058a3
XGB - Queen of ML, (generally) second best to DL
Ethics in NLP
Papers & lectures
Sources and reading...
The reality of ML/DL projects
Machine Learning: The High-Interest Credit Card of Technical Debt
This guy kind of nails it in a useful high level way
data-scientist-and-ml-engineers-are-luxury-employees
Deep learning full stack development
Measuring performance