How (and which) MLOps platforms can support your Machine Learning?


Data Scientists are confronted with numerous challenges that can prevent the succesful deployment of their projects. To address these challenges, machine learning workflow tools have been developed, focused on managing the entire ML lifecycle and supporting its users.
However, as these tools are relatively new, there is currently no standard among these tools, making it difficult to decide which tool serves which purpose the best.

In this white paper we propose a framework that can be used to compare ML workflow tools, allowing users to identify their strengths & weaknesses.

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