PinnedMark EltsefoninTowards Data ScienceCommon Mistakes During A/B TestingOur path to excellence is paved with mistakes. Let’s make them!·5 min read·Apr 24, 2022--3--3
Mark EltsefonBuilding connections for A/B testing and linear regressionLinear regression or T-test. How to choose ?·5 min read·Dec 27, 2023----
Mark EltsefoninStartup StashUplift Models. Let’s Measure Them!Can we just use precision and recall for uplift models or we have to invent something ?·5 min read·Jul 11, 2023--1--1
Mark EltsefoninTowards Data ScienceChoosing the Right Path: Churn Models vs. Uplift ModelsDo we really need churn models? Maybe uplift modelling can give us more comprehensive answer?·5 min read·Jun 16, 2023--2--2
Mark EltsefoninBetter ProgrammingNew Panda..s has comeLet’s discuss one of the most widely used libraries in the field of data science — Pandas.·4 min read·Apr 22, 2023----
Mark EltsefoninTowards Data ScienceCommon AB testing mistakes. Vol 2Let’s learn from our mistakes!·4 min read·Apr 13, 2023--2--2
Mark EltsefoninTowards Data ScienceSeasoning your AB testing experimentsHow can salt help you with experiments?·5 min read·Mar 13, 2023--2--2
Mark EltsefonBuild or not to build?Choosing how to maintain your experiments may be a tedious task·3 min read·Jan 28, 2023--1--1
Mark EltsefonWinner Winner Chicken D..ataPoker and Data science. What do they have in common?3 min read·Jan 17, 2023----
Mark EltsefonDon’t be afraid to run into novelty effect.Let’s imagine we have implemented new feature and our prime metric was time spent on site and it’s way up for test vs control.3 min read·Dec 22, 2022----