Orchestrating data for machine learning pipelines
[ad_1] Machine learning (ML) workloads require efficient infrastructure to yield rapid results. Model training relies heavily on large data sets. Funneling this data from storage to the training cluster is the first step of any ML workflow, which significantly impacts the efficiency of model training. Data and AI platform engineers have long been concerned with…