[{"command":"insert","method":"replaceWith","selector":"#related-posts","data":"\u003Cdiv class=\u0022content-box\u0022 id=\u0022related-posts\u0022\u003E\u003Cdiv class=\u0022related-posts-title\u0022\u003ERelated posts\u003C\/div\u003E\n\t\u003Cdiv class=\u0022related-posts\u0022\u003E\n\t\u003Cul\u003E\n    \n        \n           \u003Cli\u003E \u003Ca href=\u0022\/post\/iris-dockerization-and-embedded-python-data-science-\u2014-one-command-setup-reproducible-ml\u0022\u003EIRIS Dockerization and Embedded Python for Data Science \u2014 One-Command Setup for Reproducible ML Workflows\u003C\/a\u003E\u003C\/li\u003E\n           \n        \n           \u003Cli\u003E \u003Ca href=\u0022\/post\/beyond-integratedml-what-are-our-options-continuous-training-ct-iris\u0022\u003EBeyond IntegratedML: What are our options for Continuous Training (CT) in IRIS?\u003C\/a\u003E\u003C\/li\u003E\n           \n        \n           \u003Cli\u003E \u003Ca href=\u0022\/post\/complementing-iris-mlflow-continuous-training-ct-pipeline\u0022\u003EComplementing IRIS with MLflow for a Continuous Training (CT) pipeline\u003C\/a\u003E\u003C\/li\u003E\n           \n        \n           \u003Cli class=\u0022related-posts-this\u0022\u003EExplainability in ML Models\u003C\/li\u003E\n           \n     \n    \n\u003C\/ul\u003E\u003C\/div\u003E\n\n\n\u003C\/div\u003E","settings":null}]