Thanks, <@842787984902062080>. Could you elaborate...
# beginners-need-help
Thanks, @datajoely. Could you elaborate more on different parts of the run lifecycle that could possibly use hooks? I am looking at this article, and it uses Mlflow as an example, and there are two
statements in the scripts.
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if node._func_name == "split_data":
                {"split_data_ratio": inputs["params:example_test_data_ratio"]}

        elif node._func_name == "train_model":
            model = outputs["example_model"]
            mlflow.sklearn.log_model(model, "model")
These are node specific functions, Do you think these are better put in the node logic itself instead of hooks or it is a proper user case for hooks? Or as @noklam suggested using kedro-mlflow?