1. Deploying models easily (data scientist doesn't need to grok docker/kube)
2. Monitoring models including data and model drift/statistical monitoring (data scientists don't need to grok prom/grafana)
3. Only once these base concerns are met, model inventory, provenance, data versioning, reproducibility, collaboration with notebooks, ci integration etc.
Happy to talk more - drop me a note at luke@dotscience.com
2. Monitoring models including data and model drift/statistical monitoring (data scientists don't need to grok prom/grafana)
3. Only once these base concerns are met, model inventory, provenance, data versioning, reproducibility, collaboration with notebooks, ci integration etc.
Happy to talk more - drop me a note at luke@dotscience.com