. . . . . . . . . . . . "python" . . "3.9.15.final.0" . "@is_fairworkflow(label='My model training workflow')\ndef training_workflow(n_jobs):\n\n # Define models hyper params\n hyper_params = {\n 'n_jobs': n_jobs,\n 'random_state': 42\n }\n\n data = load_data()\n y = load_data_y()\n\n # Train model (here we use a stub dataset just to make the example clear)\n model = fit_classifier(hyper_params, data, y)\n\n # Evaluate the model using your own metrics\n scores = evaluate(model)\n\n # Save the model generated to the models/ folder\n path = save(\n model,\n \"models/my_model\",\n sample_data=data,\n scores=scores,\n hyper_params=hyper_params,\n )\n return path\n # Optionally you can save other files (dataframes, JSON objects) in the data/ folder\n" . . . "My model training workflow" . . . . . . . . . . . . "2022-12-21T14:40:57.515937"^^ . "RSA" . "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAlKZel+uM9w+JiWuhs0NHtaXdRrGkGAjvnnLFQL2nmgZDGIjX+is2YJBd6R2kBkr67lYiUDWdtih0F0yqUlAW5GdYUihk1MBiWyLe4RNt7I5iC/5wwK/i5vV6/YKa6Zwf4oymwChpdXddlKc6d73StgFqOafQPeNeBUHTZbkmUKFAqGXf0nAclB23DEeN5qVl6XRa1qqtL91AKW+UxTvlZR3pFNFn8xKTfbOSgmuAkYSUwJrp84rNI92qXYtOJ12oH0oT/enzcThxcfPLomGc9BMd+QBCj08LdrtuAArHzcivMKDzreDCD+haZ/GdObRWHpQ5O4bEWIx3dZVQq7t0KQIDAQAB" . "TjYWnjUeUYbEmQ28jqwsQbD6RCSFfd2CR1n/4belgkxdeGxbbNhNpGxlVeU0rM7hi3o83Anp++efrAUzwHx6xzf43Pvi4IRgmtfAxWu80Eex2cndsc4nijRuK9P6lD0vDqZXwYNneIE1n4Efiu4dNMYnE86jlOAmewvHTYO1kD11hNv3lfDYjVK7qNC52UIPLovJnAnGM22djd+p/PbN4etwXmAm8i2EPxDZs9eMPoBJqqm71os7cidqHWxot5Xhb0/EV6XngKXUGsUBYl08AukrrDO1R78PMcvT+P7PgECuIevFuUwpK2z6qMBd3f7p0bkr/4zJGd5eBbqfdfhk6A==" . . .