Name: 5 Missteps of Machine Learning Every Operations Manager Can Avoid
Start: 2020-04-28T10:00:00-04:00
End: 2020-04-28T10:30:00-04:00

Register here: https://bit.ly/3cbPM9c

Machine learning development is a tangle of tools, languages, and infrastructures, with almost no standardization at any point in the process. Manual stopgaps and one-off integrations may get models into production, but they create fragility and risk, preventing organizations from trusting ML with mission-critical applications. To build and deploy enterprise-ready models that generate real value, businesses need to standardize a new technology stack and a new ML–focused lifecycle.

Join us on Tuesday, April 28th at 10:00 AM PT to explore:

- Five major challenges every organization faces when putting machine learning applications into production and how to avoid them.
- Best practices for machine learning operations (MLOps) and management.
- Real-world examples of how organizations have made this pay off for their business.

Even if you can't make it, register anyway, and we'll send you the recording.

Register to attend: https://bit.ly/3cbPM9c

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5 Missteps of Machine Learning Every Operations Manager Can Avoid

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DSS Montreal | R User Group

5 Missteps of Machine Learning Every Operations Manager Can Avoid

DSS Montreal | R User Group

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