Throwing together ad-hoc machine learning models and proofs-of-concept is one thing, but delivering machine learning (ML) models at-scale — even on a platform like AWS — is another class of problem entirely.

Data scientists are primarily focused on optimizing models to better solve business problems, rather than ensuring those models will be performant and scalable for a given infrastructure use case; meanwhile, traditional software engineers may not be familiar with the unique combination of tools and languages that ML applications typically rely on.

AWS Machine Learning from phData gets your models into production. With leading experts on AWS ML and data technologies — and a proven track record delivering successful data products — we support you across the entire lifecycle of a machine learning project, from ideation to post-implementation support.