Yahoo Web Search

Search results

1. Top results related to valueerror: protocol not known: azureml

   • Pandas read_json ValueError: Protocol not known

     Top Answer

     Answered Aug 25, 2020 · 7 votes

     As far as I could debug this issue is caused by an update of pandas. The 1.1.0 update had changed few things on the read_json function.

     I could make my code work when setting pandas version to 1.0.5

     https://pandas.pydata.org/docs/whatsnew/v1.1.0.html

     Check all answers on Stack Overflow

     1/5

   • ValueError : Length Not Known while mapping a list in Theano

     Top Answer

     Answered Jan 01, 2015 · 1 votes

     The reason you get "Elemwise{sqrt,no_inplace}.0" is because Theano is symbolic, so tensors do not have a value until evaluated. To fix this:

     from matplotlib.pyplot import plotfrom numpy import linspaceimport theano.tensor as TA = linspace(0,1,100)plot(A, T.sqrt(A).eval())

     to evaluate the tensor and get its numeric value.

     Also, you should import theano.tensor, not theano.tensors.

     Check all answers on Stack Overflow

     2/5

   • ValueError: Not all divisions are known, can't align partitions error on dask dataframe

     Top Answer

     Answered May 14, 2019 · 1 votes

     When creating the dask dataframe add the reset_index():

     user_profile_ddf = df.from_pandas(user_profile, npartitions=4).reset_index()-

     Check all answers on Stack Overflow

     3/5

   • ValueError: unsupported pickle protocol: 3, python2 pickle can not load the file dumped by python 3 pickle?

     Top Answer

     Answered Sep 15, 2014 · 167 votes

     You should write the pickled data with a lower protocol number in Python 3. Python 3 introduced a new protocol with the number 3 (and uses it as default), so switch back to a value of 2 which can be read by Python 2.

     Check the protocolparameter in pickle.dump

     . Your resulting code will look like this.

     pickle.dump(your_object, your_file, protocol=2)-

     There is no protocolparameter in pickle.load

     because pickle can determine the protocol from the file.

     Check all answers on Stack Overflow

     4/5

   • AzureML: "Train Matchbox Recommender" is not working and does not descibe the error

     Top Answer

     Answered May 24, 2016 · 2 votes

     The matchbox recommender requires that ratings be numerical or categorical. Also when training, your ratings cannot all be the same.

     You need to use a metadata editor https://msdn.microsoft.com/en-us/library/azure/dn905986.aspx to convert the ratings into numerical features and you need to make sure you are using a range of ratings.

     Then this should work!

     Check all answers on Stack Overflow

     5/5

   Show moreShow less

2. learn.microsoft.com › en-us › answersWhat packages are needed to use a Azure URI with pandas

   learn.microsoft.com › en-us › answers

   • Cached

   Apr 24, 2023 · Accepted answer. Jimmy Briggs 101. Apr 24, 2023, 12:21 PM. Use the azureml-fsspec package: Bash. Copy. pip install azureml-fsspec. Note: The accepted URI format for the datastore URI is: azureml://subscriptions/([^/]+)/resourcegroups/([^/]+)/workspaces/([^/]+)/datastores/([^/]+)/paths/([^/]+) This should technically work: Python. Copy.

3. stackoverflow.com › questions › 63553845python - Pandas read_json ValueError: Protocol not known ...

   stackoverflow.com › questions › 63553845

   • Cached

   Aug 24, 2020 · ValueError: protocol not known. import json. temp = json.dumps([status._json for status in tweet]) # create JSON. newdf = pd.read_json(temp, orient='records') python. pandas. edited Jul 19, 2022 at 12:18. tuomastik. 4,749 5 40 50. asked Aug 24, 2020 at 2:05. Jason. 467 2 4 13. Can you share your json temp ? – Psidom. Aug 24, 2020 at 2:55.

   Code sample

   from io import StringIO

   newdf = pd.read_json(StringIO(temp))

   See more on stackoverflow

4. github.com › Azure › azure-sdk-for-python[Azure ML SDK v2] Issue while reading data from - GitHub

   github.com › Azure › azure-sdk-for-python

   • Cached

   Mar 9, 2013 · Operating System: Windows Server 2022 Standard. Python Version: 3.9.13. Describe the bug. According to the documentation it should be possible to access public blob storage containers using Input(type='uri_folder') instance. While passing actual path of the data, azure docs say that it is possible to use either. https://<account_name>.blob.core ...

5. People also ask

   How do I run a published pipeline in azureml?

   • To publish and run your experiment: You can run the published pipeline immediately using published_pipeline.submit. Or at any time you can run a published pipeline via the AzureML studio by going to "Pipelines" > "Pipeline endpoints" to see a list of all the published pipelines in your AzureML workspace.

   The missing guide to AzureML, Part 3: Connecting to data and running

   drivendata.co/blog/missing-guide-to-azureml-part3-connecting-to-data-and-running/

   See all results for this question

   How do I run an experiment in azureml?

   • There are two ways to run your pipeline. The first is to simply call pipeline.submit( ) to initiate a one-off run of your pipeline. The second is to "publish" your experiment to your AzureML workspace, saving it so that you can run it again and again. To publish and run your experiment:

   The missing guide to AzureML, Part 3: Connecting to data and running

   drivendata.co/blog/missing-guide-to-azureml-part3-connecting-to-data-and-running/

   See all results for this question

   How do I use metrics in azureml?

   • We'll also cover how to log metrics to show up on your AzureML studio dashboard and how to use parameters to make flexible, reusable pipelines. The simplest way to work with data in AzureML is to read and write blobs from the blob datastore attached to your AzureML workspace.

   The missing guide to AzureML, Part 3: Connecting to data and running

   drivendata.co/blog/missing-guide-to-azureml-part3-connecting-to-data-and-running/

   See all results for this question

   Where should script Py be stored in azureml?

   • The official best practice, as documented in the Getting Started notebook, is to save script.py in its own subdirectory, which apparently allows the step to be snapshotted more efficiently within AzureML. The resulting directory structure should look like this:

   The missing guide to AzureML, Part 3: Connecting to data and running

   drivendata.co/blog/missing-guide-to-azureml-part3-connecting-to-data-and-running/

   See all results for this question

6. drivendata.co › blog › missing-guide-to-azureml-partThe missing guide to AzureML, Part 3: Connecting to data and ...

   drivendata.co › blog › missing-guide-to-azureml-part

   • Cached

   Jul 21, 2020 · Azure Pipelines and AzureML together can result in some powerful MLOps workflows: for example, whenever new model code is pushed to our repository, automatically run a pipeline to: 1) check code quality and run unit tests, 2) publish test coverage reports, 3) retrain a model, 4) evaluate the model on held-out data, 5) if the model outperforms ...

7. learn.microsoft.com › en-us › azureTroubleshooting online endpoints deployment - Azure Machine ...

   learn.microsoft.com › en-us › azure

   • Cached

   kubectl exec -it deploy/azureml-fe -- /bin/bash (Run in azureml-fe pod) curl -vi -k https://localhost:<port>/api/v1/endpoint/<endpoint-name>/swagger.json "Swagger not found" For HTTP, use. curl https://localhost:<port>/api/v1/endpoint/<endpoint-name>/swagger.json "Swagger not found"

8. azureml-examples.readthedocs.io › en › latestGetting Started with Azure Machine Learning Python SDK

   azureml-examples.readthedocs.io › en › latest

   • Cached

   azureml-examples Navigation. Contents: Overview; Getting Started with Azure Machine Learning Python SDK. Prerequisites; Set up; Getting started; Examples; Using MLflow with Azure Machine Learning; Working with Azure AI ML; Working with Numpy; Working with XGBoost; Contributing to Azure Automated Machine Learning Samples; Working with Azure ...

9. azure.github.io › azureml-sdk-for-r › articlesKnown issues and troubleshooting • azuremlsdk - GitHub Pages

   azure.github.io › azureml-sdk-for-r › articles

   • Cached

   The error will look as follows: Installing package into '/usr/local/lib/R/site-library' (as 'lib' is unspecified) Warning message in install.packages(<package name>): "'lib = "/usr/local/lib/R/site-library"' is not writable" The discrepancy is due to RStudio assuming a different default library location than the R kernel in Jupyter.