Streamlining Experimentation
Experimentation tools have traditionally focused on marketing and web design, leaving gaps in testing backend changes like pricing algorithms. EPO addresses this by providing a comprehensive statistical engine and user-friendly analysis interface, significantly reducing the time data scientists spend managing experiments. This innovation makes experimentation more accessible and efficient for companies of all sizes.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
SDS 601: Venture Capital for Data Science — with Sarah Catanzaro
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