90% of all AI models fail to deliver value. Why is that?
With massive investments in data science teams, platforms, and infrastructure, the number of AI projects is dramatically increasing — along with the number of missed opportunities. Unfortunately, most projects are not showing the value that the business expects, and new risks are introduced that need to be managed. In this session you will gain an understanding of these challenges, why it’s important and how to overcome them with MLOps. Attend to:
Key takeaways
- Learn how global organisations are utilising data scientist and data engineers in tandem for AI success
- Understand why monitoring and management of machine learning models is crucial for governance goals and immediate value
- See where and when technology can help
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