The first and most important step towards developing a powerful machine learning model is acquiring good data. It doesn’t matter if you’re using a simple logistic regression or the fanciest state-of-the-art neural network to make predictions: If you don’t have rich input, your model will be garbage in, garbage out. This exposes an unfortunate truth that every hopeful, young data scientist has to c
The goal of lda2vec is to make volumes of text useful to humans (not machines!) while still keeping the model simple to modify. It learns the powerful word representations in word2vec while jointly constructing human-interpretable LDA document representations. We fed our hybrid lda2vec algorithm (docs, code and paper ) every Hacker News comment through 2015. The results reveal what topics and tren
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