aws / aws/amazon-sagemaker-examples
[Content Improvement] stdout from wget in Machine Translation English-German Example Using SageMaker Seq2Seq
- Dominant language
- Jupyter Notebook
- Stars
- 11k
- Forks
- 7k
- Avg merge
- 8h 29m
- Merged PRs (30d)
- 8
Description
**Link to the notebook**
[Machine Translation English-German Example Using SageMaker Seq2Seq](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/seq2seq_translation_en-de/SageMaker-Seq2Seq-Translation-English-German.html)
**What aspects of the notebook can be improved?◇
This notebook has an extreme (about 250 pages A4) amount of stdout from the `wget` command used to download the dataset. Since this is at the beginning of the notebook, users have to scroll through all of this to view the actual content.
**What are your suggestions?**
* use the `-q` switch for wget to suppress the output
* (add a sanity check to the build process to automatically prevent this from happening again?)
Contributor guide
Research direction
Open the linked Machine Translation English-German notebook and find the dataset-download cell using wget. Suppress wget's output as suggested, then rerun or render the notebook and confirm the excessive stdout is gone; the build-process sanity check can be assessed separately.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, jupyter-notebook
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 1/5
- Estimated time
- Under an hour
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 45/100