Published inMercado Libre Tech#10 — The key success factor in ML projectsTo have a thorough knowledge of the domainNov 18, 20211Nov 18, 20211
Published inMercado Libre Tech#9 — Train serving skew & data dependency problemsHow to mitigate risks from data problems in productive machine learning modelsNov 18, 2021Nov 18, 2021
Published inMercado Libre Tech#8 — Continuous Benchmark in ML projectsThe importance of enabling the competition to improve the final product.Oct 22, 2021Oct 22, 2021
Published inMercado Libre Tech#7 — Are your Problems Similar to those of the Rest of the Industry?The question is: Can the components of your ML current solution be commoditized?Oct 14, 2021Oct 14, 2021
Published inMercado Libre Tech#6 — The key for data science projects: Stand Close to the UserTime investment is correct, but only if time is invested in the generation of short or long term value for the user.Sep 17, 2021Sep 17, 2021
Published inMercado Libre Tech#5 — Any Machine Learning Project, is a Software Project FirstThis explanation may seem unnecessary; not in my experience, though.Aug 19, 20211Aug 19, 20211
Published inMercado Libre Tech#4 — Be accountable for the Tech DebtLet’s find out how much technical debt do your machine learning projects have with this game.Jul 30, 2021Jul 30, 2021
Published inMercado Libre Tech#3 — This is why you are not iterating your ML project fast enoughStop delaying that deploy, take risks to base decisions on production metricsJun 10, 20213Jun 10, 20213
Published inMercado Libre Tech#2 — Skills diversity: Building the right machine learning teamA view of the differents skills needed for develop a successful ML projectMay 27, 2021May 27, 2021
Published inMercado Libre Tech#1 — No Machine Learning. KPIs firstThe importance and complexity of designing good KPIs in a Machine Learning project.May 19, 20214May 19, 20214
