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Basics of ML experiments metrics & artifacts tracking with MLflow

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Preparation

Clone this repository

https://gitlab.com/7labs.ru/tutorials/mlflow-1-tracking

cd mlflow-1-tracking

2. Create .env file in config/ folder

GIT_CONFIG_USER_NAME=<git user>
GIT_CONFIG_EMAIL=<git email>

example

GIT_CONFIG_USER_NAME=mnrozhkov
[email protected]

Get data

Download iris.csv

wget -P data/raw/ -nc https://raw.githubusercontent.com/uiuc-cse/data-fa14/gh-pages/data/iris.csv

Build image

ln -sf config/.env && docker-compose build

Run container

docker-compose up

Start tutorial

Open JupyterLab

http://0.0.0.0:8888

Open mlflow ui

http://0.0.0.0:5000

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Basics of ML experiments metrics & artifacts tracking with MLflow

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