Remove 2013 Remove Experimentation Remove Modeling Remove Statistics
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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. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate. And sometimes even if it is not[1].)

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

Insight

In 2013, Robert Galbraith?—?an The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. More relevant to the AIgent is Google’s BERT model, a task-agnostic (i.e. an aspiring author?—?finished

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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.