Scale
06/12/2018 - 11:00 to 11:40
Maschinenhaus
long talk (40 min)
Intermediate
Session abstract:
- How does one build a pyspark model and deploy it in a scala pipeline with no code rewrite - Solving the greatest fights between datascientist who want to code in python and data engineers who like the tried and tested type safety of the JVM.
- How does one beat the spark context latency to serve spark models in milliseconds to handle near realtime business needs
- How does one build a ML model, zip it up and deploy it across platforms in a completely vendor neutral way i.e. build your model on AWS and deploy it on GCP or vice-versa.
- How does one leverage the years of efforts spent in software engineering and use it directly in building datascience pipelines without reinventing the wheel and pain.
- How does on build a completely GDPR compliant machine learning model with 0.88 on the ROC curve.
