Multi-cloudAdvancedMachine Learning
ML Infrastructure in Production
What happens to a model after the notebook closes: pipelines, serving, drift, and the accelerator economics nobody budgets for.
$64
Elena Varga
ML Infrastructure Engineer
Elena builds the training and serving substrate under production recommendation systems. She is interested in what happens to models after the notebook closes.
2 titles · 770 pages in print
Titles by Elena Varga
- Google CloudPractitionerData
Data Engineering on GCP
With Priya Raghunathan
Streaming and batch pipelines on Google Cloud, with windowing and late data treated as first-class problems.
$59