DEM52-S: Battle-tested tactics to accelerate data science and ML R&D with AWS

AWS re:Invent 2019

While software engineers benefit from a mature tooling ecosystem, data scientists often aren't as lucky. To add to this challenge, data science typically requires tight integration with infrastructure to handle large amounts of data and computation, even during early research and development (R&D) stages. In this session, Gabriel Bianconi from Toptal draws from his experience as a machine learning (ML) consultant and walks you through the behind-the-scenes aspects of successful case studies as well as lessons learned from failed experiments. Solutions that enable practitioners to prototype and iterate more quickly while taking on less technical debt are of particular focus. This presentation is brought to you by Toptal, an APN Partner.