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apply() Conference 2021 | ML Design Patterns for Data Engineers
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ML Design Patterns for Data Engineers
by:
Valliappa Lakshmanan, Director, Google
As machine learning moves from being a research discipline to a software one, it is useful to catalog tried-and-proven methods to help engineers tackle frequently occurring problems that crop up during the ML process. In this talk, I will cover three patterns that are useful in creating large-scale and resilient data and ML pipelines. These patterns provide a way to apply hard-won knowledge from hundreds of ML experts to your own projects.
apply(): The ML data engineering Conference
Presented by Tecton
Connect with us:
by:
Valliappa Lakshmanan, Director, Google
As machine learning moves from being a research discipline to a software one, it is useful to catalog tried-and-proven methods to help engineers tackle frequently occurring problems that crop up during the ML process. In this talk, I will cover three patterns that are useful in creating large-scale and resilient data and ML pipelines. These patterns provide a way to apply hard-won knowledge from hundreds of ML experts to your own projects.
apply(): The ML data engineering Conference
Presented by Tecton
Connect with us:
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