Remove 2013 Remove Experimentation Remove Statistics Remove Testing
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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. And we can keep repeating this approach, relying on intuition and luck. Why experiment with several parameters concurrently?

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The AIgent: Using Google’s BERT Language Model to Connect Writers & Representation

Insight

In 2013, Robert Galbraith?—?an The most powerful approach for the first task is to use a ‘language model’ (LM), i.e. a statistical model of natural language. I tested several different flavors of BERT for use as synopsis classifiers before settling on the DistilBERT model from Hugging Face. an aspiring author?—?finished

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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Although it’s not perfect, [Note: These are statistical approximations, of course!] Note: A test set of 19,500 such analogies was developed by Tomas Mikolov and his colleagues in their 2013 word2vec paper. This test set is available at download.tensorflow.org/data/questions-words.txt.]. Example 11.6 Note: Mikolov, T.,