ML Design Patterns for Data Engineers

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.