Deep Learning brings with it enormous amounts of data, complicated experiment results and intense compute requirements. Decades of experience in moving code to production yielded best practices in engineering that have not yet found their place in deep learning teams. Over the past few years, the term “DevOps” has become an industry standard but where are the deep learning best practices for AI First companies?
On July 17th, I’ll be speaking at Reversim in Tel Aviv to discuss how the deep learning field can adopt the techniques developers have been taking advantage of for years such as continuous integration, managing large amounts of data, and application monitoring by implementing DeepOps – deep learning operations. DeepOps is a set of methodologies, tools, and culture where data engineers and scientists collaborate to build a faster and more reliable deep learning pipeline.
I’m looking forward to sharing some of the insights we’ve learned by speaking to over a hundred AI companies to better understand their deep learning workflows better. Hope to see you there!