azure-machine-learning-studio

I am working on Azure ML implementation on text analytics with NLTK, the following execution is throwing AssertionError: 1 columns passed, passed data had 2 columns\r\nProcess returned with non-zero exit code 1 Below is the code # The script MUST include the following function, # which is the entry point for this module: # Param<dataframe1>: a pandas.DataFrame # Param<dataframe2>: a pandas.DataFrame def azureml_main(dataframe1 = None, dataframe2 = None): # import required packages import pandas as pd import nltk import numpy as np # tokenize the review text and store the word corpus word_dict

4 years ago I posted this question and got a few answers that were unfortunately outside my skill level. I just attended a build tour conference where they spoke about machine learning and this got me thinking of the possibility of using ML as a solution to my problem. i found this on the azure site but i dont think it will help me because its scope is pretty narrow. Here is what i am trying to achieve: i have a source image: and i want to which one of the following symbols (if any) are contained in the image above: the compare needs to support minor distortion, scaling, color differences,

I am moving data into Azure Data Lake Store and processing it using Azure Data Lake Analytics. Data is in form of XML and I am reading it through XML Extractor . Now I want to access this data from Azure ML and it looks like Azure Data Lake store is not directly supported at the moment. What are the possible ways to use Azure Data Lake Store with Azure ML? Right now, Azure Data Lake Store is not a supported source, as you note. That said, Azure Data Lake Analytics can also be used to write data out to Azure Blob Store, and so you can use that as an approach to process the data in U-SQL and

I am new to Azure ML. I am having some doubts .Could anyone please clarify my doubts listed below. What is the difference between Azure ML service Azure ML experimentation service. What is the difference between Azure ML workbench and Azure ML Studio. I want to use azure ML Experimentation service for building few models and creating web API's. Is it possible to do the same with ML studio. And also ML Experimentation service requires me to have a docker for windows installed for creating web services. Can i create web services without using docker? The AML Experimentation is one of our many

I have a number of large csv (tab delimited) data stored as azure blobs, and I want to create a pandas dataframe from these. I can do this locally as follows: from azure.storage.blob import BlobService import pandas as pd import os.path STORAGEACCOUNTNAME= 'account_name' STORAGEACCOUNTKEY= "key" LOCALFILENAME= 'path/to.csv' CONTAINERNAME= 'container_name' BLOBNAME= 'bloby_data/000000_0' blob_service = BlobService(account_name=STORAGEACCOUNTNAME, account_key=STORAGEACCOUNTKEY) # Only get a local copy if haven't already got it if not os.path.isfile(LOCALFILENAME): blob_service.get_blob_to_path

In execute python module. The line import humanfriendly gives error. How to fix this? Your description is not clear, I don't know what happended when you got error via import humanfriendly as you said. So I just can do for you that only post my steps about how to install humanfriendly Python package in Azure ML, as below. According to the section Technical Notes of the document "Execute Python Script", I download the humanfriendly package from here . I decompressed the package (the same for either .whl file or .tar.gz file), and package its humanfriendly directory as a zip file. Then I click