Managing the end-to-end machine learning lifecycle with MLFlow

This Repository contains the resources for my tutorial "Managing the end-to-end machine learning lifecycle with MLFlow" at pyData/pyCon Berlin 2019.

Basic setup

Setup the environment

• clone this repository

• with virtualenv (recommended)

  • install virtualenv: pip install virtualenv
  • create a new environment: virtualenv mlflow_tutorial
  • activate the environment: source mlflow_tutorial/bin/activate
  • run pip install -r requirements.txt

• with pipenv

  • install pipenv: pip install pipenv
  • run pipenv install in the directory of the Pipfile
  • activate the environment by pipenv shell

The notebook

• Get the hands_on_example.ipynb
• run jupyter notebook

Advanced setup

Setup the environment

• install postgresql: sudo apt-get install postgresql postgresql-contrib postgresql-server-dev-all