azure-machine-learning-studio

AzureML's Python Script module requires to return a Pandas DataFrame. I want to return only a value and I do this: result=7 dataframe1=pd.DataFrame(numpy.zeros(1)) dataframe1[0][0]=result by which I am able to return just a single value in Azure ML's Python Script module. What is a proper way to create a pandas DataFrame with a single value? Following code should work: import pandas as pd def azureml_main(dataframe1 = None, dataframe2 = None): result = pd.DataFrame({'mycol': [123]}) return result, As EdChum commented dataframe1=pd.DataFrame([result], dtype=float) and it works, tested, instead

I've created some Azure Machine Learning Workspaces and associated them with "classic" storage accounts; but would like to have them associated with "not-classic" (or whatever the term is) storage accounts. Is there a way to convert the storage accounts from "classic", or to change the storage account associated with a Machine Learning Workspace? As of today, there's no automatic way of converting a "Classic" storage account into "Azure Resource Manager (ARM)" storage account. Today, you would need to copy data from a classic storage account to a new storage account. Having said that, there's

I have created a csv file, with no header. its 1496 rows of data, on 2 columns in the form: Real; String example: 0.24; "Some very long string" I go to New - Dataset - From local file Pick my file, and No header csv format But after its done loading i get an error message i cant decrypt: Dataset upload failed. Internal Service Error. Request ID: ca378649-009b-4ee6-b2c2-87d93d4549d7 2015-06-29 18:33:14Z Any idea what is going wrong? At this time Azure Machine Learning only accepts the comma , seperated, American style CSV. You will need to convert to a comma separated CSV 来源： https:/

I am working on the Walmart Kaggle competition and I'm trying to create a dummy column of of the "FinelineNumber" column. For context, df.shape returns (647054, 7) . I am trying to make a dummy column for df['FinelineNumber'] , which has 5,196 unique values. The results should be a dataframe of shape (647054, 5196) , which I then plan to concat to the original dataframe. Nearly every time I run fineline_dummies = pd.get_dummies(df['FinelineNumber'], prefix='fl') , I get the following error message The kernel appears to have died. It will restart automatically. I am running python 2.7 in

I just wanted to test how good can neural network approximate multiplication function (regression task). I am using Azure Machine Learning Studio. I have 6500 samples, 1 hidden layer (I have tested 5 /30 /100 neurons per hidden layer), no normalization. And default parameters Learning rate - 0.005, Number of learning iterations - 200, The initial learning weigh - 0.1, The momentum - 0 [description] . I got extremely bad accuracy, close to 0. At the same time boosted Decision forest regression shows very good approximation. What am I doing wrong? This task should be very easy for NN. Big

In Azure ML, I'm trying to execute a Python module that needs to import the module pyxdameraulevenshtein ( https://pypi.python.org/pypi/pyxDamerauLevenshtein ). I followed the usual way, which is to create a zip file and then import it; however for this specific module, it seems to never be able to find it. The error message is as usual: ImportError: No module named 'pyxdameraulevenshtein' Has anyone included this pyxdameraulevenshtein module in Azure ML with success ? (I took the package from https://pypi.python.org/pypi/pyxDamerauLevenshtein .) Thanks for any help you can provide, PH I