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Word embeddings are vector representations of words, where more similar words will have similar locations in vector space. First developed by a team of researchers at Google led by Thomas Mikolov, and discussed in the paper Efficient Estimation of Word Representations in Vector Space, word2vec is a popular group of models that produce word embeddings by training shallow neural networks. In this blog post, we apply a word2vec model to the Alteryx Community texts to develop Alteryx-specific word embeddings.
Ever wondered how to build a new analytic tool from scratch using the Alteryx Python SDK, but didn’t know where to start? This blog post takes you through the absolute basics to get you up and running - You’ll be creating brand new tools, connectors and advanced analytics in no time with this step-by-step beginners guide!