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Jupyter notebook presenting the lifecycle of a ML model for the recommendations scenario example.

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Setup

Make sure the Anaconda distribution is installed on your machine.

  1. Create and activate a new conda environment with Python 3.10
$ conda create -n <environment_name> python=3.10
$ conda activate <environment_name>
  1. Install dependencies
  • recommenders - pip install recommenders
  • mlflow - conda install mlflow; make sure the installed version is at least 2.16 to avoid problems with Databricks integration that are present in older versions
  • tensorflow - pip install tensorflow==2.12.0
  1. Run Jupyter Notebook
jupyter notebook
  1. Deactivate the conda environment when finished:
$ conda deactivate

To completely remove the conda environment execute:

$ conda remove -n <environment_name> --all

Development

Once the conda <environment_name> has been successfully set up, the only requirement is to activate that environment:

$ conda activate <environment_name>

and (usually) starting the Jupyter Notebook:

jupyter notebook

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Jupyter notebook presenting the lifecycle of a ML model for the recommendations scenario example.

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