re: Supervised Learning: Instance-based Learning and K-Nearest Neighbors VIEW POST

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re: Depending on the number of dimensions you can try an embedding (word2vec, gloVe, fastText, ...) or something like a dimensionality reduction (PCA, ...
 

thanks - i'm very keen on NLP type problems and unfortunately it doesnt seem to be covered in any detail in this course. so after i end this series i may do a further deep dive on this, or maybe if you wanna write up some things i can explore (a pseudo syllabus?) i will happily do that

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