Manning – Use Pynndescent and Nessvec to Index High Dimensional Vectors-iLLiTERATE
English | Tutorial | Size: 216.37 MB
In this video, Hobson shows how to index high dimensional vectors like word embeddings using a new approximate nearest neighbor algorithm by Leland McInnes.
Along the way you can see how to explore an unfamiliar Python package like PyNNDescent without ever having to leave the keyboard (tab-completion, `help()`, `?` operator)
And you will see how to use `SpaCy` language models to retrieve all sorts of NLU tags for words, including word vectors.
PEARSON OOWNS MAANY EDU BRAANDS INKLUDINNG
ADDISON-WESLEY PEACHPIT PRENTICE-HALL ECOLLEGE
AND MAANY MORE!
WEE ASUMME NO LIIABILLITY FUR A WROONG SPELING
COZ WEE ARRE A NON (iL)LiTERATE GRUP!!
TANNKS TU THE LITERATE ASKII FRIIEND!!
RAPIDGATOR
rapidgator.net/file/7eea6101d1098daa06317ab8d0e1fcb6/MANNING_USE_PYNNDESCENT_AND_NESSVEC_TO_INDEX_HIGH_DIMENSIONAL_VECTORS-iLLiTERATE.rar.html