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updated README.md

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Tomasz Dłuski
2020-08-24 00:21:05 +02:00
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@@ -4,9 +4,7 @@ If you want to boot up mlflow project with one-liner - this repo is for you.
The only requirement is docker installed on your system and we are going to use Bash on linux/windows. The only requirement is docker installed on your system and we are going to use Bash on linux/windows.
AWS S3 based [on this article ](https://dev.to/goodidea/how-to-fake-aws-locally-with-localstack-27me) ## Step by step guide
1. Configure `.env` file for your choice 1. Configure `.env` file for your choice
2. Create mlflow bucket. You can do it **either using AWS CLI or Python Api** 2. Create mlflow bucket. You can do it **either using AWS CLI or Python Api**
@@ -53,6 +51,8 @@ s3Client.make_bucket('mlflow')
</details> </details>
---
3. Open up http://localhost:5000/#/ for MlFlow, and http://localhost:9000/minio/mlflow/ for S3 bucket (you artifacts) with credentials from `.env` file 3. Open up http://localhost:5000/#/ for MlFlow, and http://localhost:9000/minio/mlflow/ for S3 bucket (you artifacts) with credentials from `.env` file
4. Configure your client-side 4. Configure your client-side