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Data Engineering
Join discussions on data engineering best practices, architectures, and optimization strategies within the Databricks Community. Exchange insights and solutions with fellow data engineers.
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Forum Posts

Joey
by New Contributor II
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How to fix the error on INVALID_PARAMETER_VALUE when using mlflow for tracking a yolo model training?

I'm new to databricks, and I'm trying to train yolo model and use mlflow to track the parameters and log the models. I keep getting this error related to the requirements.txt file path: INVALID_PARAMETER_VALUE: Invalid value '/Shared/YOLOv8/requireme...

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Joey
New Contributor II
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Thanks for the reply, @Suteja Kanuri​ . I tried the proposed solution. This time got this message:Invalid artifact path: '/Shared/YOLOv8'. Names may be treated as files in certain cases, and must not resolve to other names when treated as such. This ...

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lewit
by New Contributor II
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Is it possible to create a feature store training set directly from a feature store table?

Rather than joining features from different tables, I just wanted to use a single feature store table and select some of its features, but still log the model in the feature store. The problem I am facing is that I do not know how to create the train...

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Debayan
Databricks Employee
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Hi, Could you please refer https://docs.databricks.com/machine-learning/feature-store/train-models-with-feature-store.html#create-a-trainingset-using-the-same-feature-multiple-times and let us know if this helps.

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rubenteixeira
by New Contributor III
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Can't parallelize model training with sc.parallelize, even tough I can run the same code without parallelizing

I'm training a NeuralProphet for a time series forecasting problem. I'm trying to parallelize my training, but this error is appearingThe folder lightning_logs has a hparams.yaml but it's empty. Is this related to permissions on the cluster? Thanks i...

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Debayan
Databricks Employee
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Hi,Please let us know if this was checked already:

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Joseph_B
by Databricks Employee
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How can I use Databricks to "automagically" distribute scikit-learn model training?

Is there a way to automatically distribute training and model tuning across a Spark cluster, if I want to keep using scikit-learn?

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Joseph_B
Databricks Employee
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It depends on what you mean by "automagically."If you want to keep using scikit-learn, there are ways to distribute parts of training and tuning with minimal effort. However, there is no "magic" way to distribute training an individual model in scik...

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