Has anyone implemented a Computer Vision solution that will find particulates in a clear liquid? Would like to hear pluses / minuses with the implementation.
When it comes to organizing your teams, how do you make sure you’re maximizing the capabilities of your data scientists within the enterprise? What is the best way to support innovation that leads to value?
What is the ideal ratio for Data Engineers to Data Scientists to ML Engineers to Product Managers? What ratio works at your organization and why?
Why are machine learning (ML) and data science teams reporting to the CTO?
Is anyone using the company KeystoneAI for your data science or AI work? Wondering what your thoughts are on the company and if they can scale a solution for an enterprise.
How do you balance model accuracy and explainability?
How do you ensure that data quality projects are accurately scoped?