Published inTDS ArchiveMachine Learning Incidents in AdTechChallenges with deep learning in productionJan 29Jan 29
Published inTDS ArchiveDeep Learning for Click Prediction in Mobile AdTechMachine Learning for Real-Time BiddingJan 23Jan 23
Published inTDS Archive10 Technologies I Explored as an Applied Data Scientist in 2021ML for ad technology and diving into deep learningDec 13, 20212Dec 13, 20212
Published inTDS ArchiveApproaches for Building Real-Time ML SystemsResponding to Prediction Requests in MillisecondsSep 7, 2021Sep 7, 2021
Published inTDS ArchiveTechnologies for Applied Data ScienceTools for building real-time ML applicationsJun 14, 2021Jun 14, 2021
Published inTDS Archive8 New Tools I Learned as a Data Scientist in 2020Making the move from Docker to Live DeploymentsDec 28, 20201Dec 28, 20201
Published inTDS ArchiveData Science in a Serverless WorldBuilding Data Products with Managed ServicesNov 9, 20202Nov 9, 20202
Published inTDS ArchiveNoSQL for Real-Time Feature Engineering and ML ModelsBuilding User Profiles with Streaming DataSep 7, 2020Sep 7, 2020
Published inTDS ArchiveDemocratizing PySpark for Mobile Game PublishingZynga Analytics at Spark Summit 2020Sep 3, 2020Sep 3, 2020
Published inTDS ArchiveWhen to use Java as a Data ScientistWhile Python and R provide rich ecosystems for data scientists to handle a wide range of problems, there are situations in which other…Aug 15, 20202Aug 15, 20202