ML Infrastructure Part 3:
Connectivity

Machine learning projects start to generate value only after workflows connect with data and related management systems.

As such, ML infrastructure must be able to adapt quickly and connect seamlessly as data scientists experiment with newer and better tools and processes.


 

Don't let your ML projects stall. 

Use this whitepaper to ensure the functional groups in your machine learning projects connect and align. 

Connectivity

Building on parts 1 and 2 of our ML Infrastructure whitepaper series, part 3 dives into the components of successful connectivity for the machine learning life cycle.

Explore the functional groupings:

  • Data and Data Management Systems
  • Training Platforms and Frameworks
  • Serving and Life Cycle Management
  • External Systems

Ensure your ML program is balancing all four.

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