aws / aws/sagemaker-training-toolkit
how to pass predictor script for running batch transformers.
- Dominant language
- Python
- Stars
- 530
- Forks
- 140
- Avg merge
- 1h 12m
- Merged PRs (30d)
- 2
Description
**What did you find confusing? Please describe.**
I have custom Catboost model created through the approach , where i am doing some pre-processing before training data.
Request: Do we have any documentation on how pass the customer predictor script to carry out the transformer job on the created estimator???
Contributor guide
Research direction
Start by locating the documentation for SageMaker batch transformer jobs and custom predictor scripts, then check how created estimators and preprocessing are described. Done means documenting the supported way to pass a customer predictor script for a CatBoost estimator during a transformer job.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, docker, machine-learning, python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100