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MLFLOW_TRACKING_URI=https://dagshub.com/priyatoshanand/mlflow_demo.mlflow MLFLOW_TRACKING_USERNAME=priyatoshanand MLFLOW_TRACKING_PASSWORD=6e371efbbbe275457498b60ef3c17d17176dcf3b python script.py
export MLFLOW_TRACKING_URI=https://dagshub.com/priyatoshanand/mlflow_demo.mlflow
export MLFLOW_TRACKING_USERNAME=priyatoshanand
export MLFLOW_TRACKING_PASSWORD=6e371efbbbe275457498b60ef3c17d17176dcf3b
Login to AWS console. Create IAM user with AdministratorAccess Export the credentials in your AWS CLI by running "aws configure" Create a s3 bucket Create EC2 machine (Ubuntu) & add Security groups 5000 port Run the following command on EC2 machine
sudo apt update
sudo apt install python3-pip
sudo pip3 install pipenv
sudo pip3 install virtualenv
mkdir mlflow
cd mlflow
pipenv install mlflow
pipenv install awscli
pipenv install boto3
pipenv shell
aws configure
#Finally mlflow server -h 0.0.0.0 --default-artifact-root s3://mlflow-06
#open Public IPv4 DNS to the port 5000
#set uri in your local terminal and in your code export MLFLOW_TRACKING_URI=http://ec2-52-207-218-138.compute-1.amazonaws.com:5000/
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Are you sure you want to delete this access key?
Are you sure you want to delete this access key?
Are you sure you want to delete this access key?
Are you sure you want to delete this access key?