Industrialization of DS/ML

Data, and data science in general, is rapidly becoming an important aspect in any organisation. And just like you want a clean, organised kitchen to work in, it is essential to prevent a sprawl of machine learning models, datasets and scripts in your environment.

Typical pain points

  • Deploying ML-algorithms on a cloud environment
  • The need for a consolidated & performant environment where data and code can live
  • Having to regularly re-train algorithms with unseen data
  • Working with datasets that are too big to handle on your local machine
  • Making real-time predictions, and streaming them to an operational team

With several exciting solutions on the market today, we are happy to discuss what works best for you.

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