mlflow / mlflow/mlflow-example
Unable to make merge request--Update README
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Description
Hello,
I just wanted to provide the following to update the README.md file. Since I was unauthorized to make a merge request, thought I would post it here.
Cheers!
(Also included the README.md file as a txt, just in case)
Example MLflow project
Overview
This is an example MLflow project for the MLflow Quickstart
documentation.
Using both the UCI Wine Quality dataset (by P. Cortez, A. Cerdeira, F.
Almeida, T. Matos and J. Reis.) and Elastic Net to predict quality, we create an MLflow project.
Moreover, The example uses MLproject to set up a Conda environment, define parameter types and defaults, entry point for training, etc.
Instructions
If you reached this repository from going through the MLflow Quickstart
documentation, please follow these instructions (else, feel free to independently go through the material yourself):
1 ) Per the Running MLflow Projects section, run the following:
mlflow run tutorial -P alpha=0.5
mlflow run git@github.com:mlflow/mlflow-example.git -P alpha=5
Note: If you are receiving git permission issues, please git clone this repository.
Thereafter, run command:
mlflow run mlflow-example -P alpha=0.5
2 ) Per the Saving and Serving Models
section, run:
python sklearn_logistic_regression/train.py
Therafter, to serve the scikit-learn model through a REST server, run:
mlflow sklearn serve -r <RUN_ID> model
Now, run
curl -d '[{"x": 1}, {"x": -1}]' -H 'Content-Type: application/json' -X POST localhost:5000/invocations
Congrats, you are done! Please refer back to the MLflow Quickstart documentation or feel free to play around more with MLflow!
Cheers!
README..txt
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading README.md and comparing it with the README text attached to this issue. Check the referenced MLflow Quickstart links and the listed commands for consistency with the example project. Done means the README contains the proposed instructions and renders correctly, with its commands and links intact.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 1/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 35/100