Quick to Production with the Best of Both Apache Spark and Tensorflow on Databricks Summit 2022

Databricks Data + AI Summit 2022

Ronny Mathew
Manager, Data Science
Rue Gilt Groupe

Using tensorflow on big datasets has previously been an impediment due to the added complexities of running it in a distributed setting and complicated MLOps code, recent advancements in tensorflow 2 and extension libraries for Spark now enables us to combine the best of both Spark and tensorflow to run distributed training of models right from Databricks notebooks with no MLOps code. This greatly reduces the time required for us to move from prototype to production by skipping the MLOps stage completely and only with the addition of a few lines in the single-node version of the code. This approach is perfect for small DS/ML teams that want to do rapid prototyping, quick experimentations, and deliver value and impact as soon as the ML development is complete.
#AI #Data #Databricks #DeltaLake #Lakehouse #MLOps

Видео Quick to Production with the Best of Both Apache Spark and Tensorflow on Databricks Summit 2022 канала Academia de Dados