I am trying to run azureml-sdk AutoML on databricks to do a feature/model sweep on a classification task, and when I run the experiment I get the following error:
Running an experiment on spark cluster: ComputeAutoML.
ERROR: Setup iteration failed: {'exception': ValueError('dataprep_json is None')}
If you are using an old SDK so upgrade to the latest SDK and pandas.
Tabular dataset need to be passed for X and y while running on ADB.
Please follow the below notebook for running automl on databricks.
https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/azure-databricks/automl/automl-databricks-local-01.ipynb
Related
How do I determine which version of Spark I'm running on Databricks? I would like to try koalas, but when I try import databricks.koalas, it returns a "No module named databricks" error message. When I try from databricks import koalas, it returns the same message.
Koalas is only included into the Databricks Runtime versions 7.x and higher. It's not included into DBR 6.x. You can find version of Databricks Runtime in the UI, if you click on dropdown on top of the notebook.
You can check version of Koalas in the Databricks Runtime release notes.
I am using the Azure Automated Machine Learning SDK to train a machine learning model on my dataset. However, after the experiment, all my training iterations fail with a KeyError: 'brand' error even if the model training itself succeeded.
How can I resolve this?
If a new environment was created after 10 June 2020 using SDK 1.7.0 or lower, training may fail with the above error due to an update in the py-cpuinfo package. (Environments created on or before 10 June 2020 are unaffected, as well as experiments run on remote compute as cached training images are used.) To work around this issue, either of the two following steps can be taken:
Update the SDK version to 1.8.0 or higher (this will also downgrade py-cpuinfo to 5.0.0):
pip install --upgrade azureml-sdk[automl]
Downgrade the installed version of py-cpuinfo to 5.0.0:
pip install py-cpuinfo==5.0.0
I was creating a recommendation engine in IBM Watson studio for that I needed to add spark service but now it is deprecated what I should use now.
You should utilize spark environments for your Watson studio project.
You can define that spark environment using Environments tab in project and then utilize that runtime when you create notebook or change service for existing notebook.
#Veer as #charles said Spark services are now accessible via Environments. When creating a notebook select a Spark compatible environment and import pyspark in your notebook.
I am new to Azure ML studio and trying to run python script.
Currently I am working on Text analytics related code and as part of that I want to get the singular values of SVD decomposition something like below
lsa=TruncatedSVD(algorithm='randomized',n_components=MaximumNumComponents,n_iter=20,random_state=42,tol=0.0)
U = lsa.fit_transform(X)
Sigma = lsa.singular_values_
Current version of scikit learn in Azure ML studio is 0.17 and singular values is part of higher versions of scikit learn like 0.20.
So I need to upgrade scikit learn package to 0.20. I tried downloading scikit learn 0.20 wheel file and zipped it and uploaded as dataset into Azure ML studio and connected enter image description here but still getting error like below "
AttributeError: 'TruncatedSVD' object has no attribute 'singular_values_'
Process returned with non-zero exit code 1
Already referred to below questions as well
Stackoverflow questions related to upgrade packages in Azure ML studio
How can I install Python packages in Azure ML?
Currently this is the limitation with Azure ML studio. The only way is to reach out to support who generates the necessary package and we can upload it to Azure ML Studio.
I am trying to run some spark scripts using execute python script in azure ML studio. And getting an error saying
unable to import spark libraries
Basically i am trying to create web services using ML studio for the models that are developed.
Is it possible or feasible to run spark jobs using ML studio?
Can anyone please help me on this.
Thanks in advance.