Ido Michael
Ido Michael co-founded Ploomber to help data scientists build faster. He'd been working at AWS leading data engineering/science teams. Single-handedly he built hundreds of data pipelines during those customer engagements together with his team. He came to NY for his MS at Columbia University. He focused on building Ploomber after he constantly found that projects dedicated about 30% of their time just to refactoring the dev work (prototype) into a production pipeline.
Sessions
In this talk we'll see how to easily run your code at scale through Docker and AWS Batch. We'll cover how to start scaling your workloads once the laptop isn't enough and how open-source can help you achieve that. ML involves training at scale to get the best performance out of the model, and at times it requires heavy-duty GPUs, which requires infrastructure work, security, permissions and operations. We'll cover the steps to deploy it without the Ops, letting you as a data scientist to focus on the important task - getting the most out of the models!