hugo bowne-andersoninTowards Data ScienceMachine Learning with the Modern Data Stack: A Case StudyConnecting DataOps with MLOps: once data is properly transformed, how is it consumed downstream to produce business value?Jul 28, 2022Jul 28, 2022
hugo bowne-andersoninTowards Data ScienceProbabilistic Machine Learning and Weak SupervisionInjecting domain expertise and probabilistic labeling into machine learning with scikit-learn: alternatives to hand labeling.Sep 4, 2021Sep 4, 2021
hugo bowne-andersoninTowards Data SciencePandas on the Cloud with DaskScaling your Pythonic data science and machine learning to the cloud using Dask. All from the comfort of your own laptop.Sep 23, 20201Sep 23, 20201
hugo bowne-andersoninCoiledThe Unbearable Challenges of Data Science At ScaleScaling Data Science is a Team SportJul 13, 2020Jul 13, 2020
hugo bowne-andersoninCoiledDistributed Data Science for IT professionalsScaling Data Science is a Team Sport: IT are Key PlayersJul 1, 2020Jul 1, 2020
hugo bowne-andersoninCoiledDistributed Computing for Data ScientistsScaling Data Science is a Team SportJun 25, 2020Jun 25, 2020
hugo bowne-andersoninTowards Data ScienceStatistical Pitfalls: Selection BiasA dialog with Mike Betancourt, in which we discuss the common statistical and data pitfall of selection bias.Apr 23, 20201Apr 23, 20201