Data Science projects are very different depending on the use-case and the industry. Several steps are important to make such projects successful and repeatable within a company. Our team has leveraged innovations coming directly from IBM Research together with our platform to tackle these projects together with our clients. This talk will cover some of these approaches and shed some light on how we could make the whole process more transparent for all the business units within the company.
Key Takeaways
- Putting Data Science into Production instead of Prototyping
- Business Innovation through structured Data Science Projects
- Trust and Fairness across the Process
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