Remove Big Data Remove Knowledge Discovery Remove Statistics Remove Testing
article thumbnail

Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. We offer two examples where this may be the case.

article thumbnail

Variance and significance in large-scale online services

The Unofficial Google Data Science Blog

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

article thumbnail

Accelerating model velocity through Snowflake Java UDF integration

Domino Data Lab

If Big Data has taught us anything, it is that with large volumes and high velocity data, it is advisable to move the computation to where the data resides. We can now test the function from our Domino Workspace (JupyterLab in this case): cur.execute("SELECT ADD(5,2)") cur.fetchone()[0]. About Domino.