We are setting up Azure ML SDK in Python. When we are creating models using Azure ML SDK in Python notebook We have to manually write the code to use feature of Azure ML and Scikit learn-- But if we model in ML studio we will do all that easily by drag and drop. Required solution is Can we build a model in Azure ML Studio and use the model in Azure ML SDK (Python Notebook). No more manual coding for Model creation will be involved. Please suggest.
#Ram mentions going from UI to Python SDK, but I recommend investigating the opposite direction with ModuleSteps in the SDK. If you can package your code into Modules, they can be called with Modules, which are on the roadmap to be made available within the visual designer.
Yes currently it's in road map to export an Azure ML Visual Designer flow into a python code. Use a graphical user interface in order to generate automatically the python code will be available in near future.
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Python has an SSM client in the Boto 3 package: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/ssm.html. Is there something similar for R? If not, any recommendations for how to make something similar? Thanks!
At the moment a package called paws on github
Access over 150 AWS services, including Machine Learning Translation
Natural Language Processing Databases File Storage
Or the cloudyr project
Welcome to the cloudyr project! The goal of this initiative is to make
cloud computing with R easier, starting with robust tools for working
with cloud computing platforms. The project’s inital work is with
Amazon Web Services, various crowdsourcing platforms, and popular
continuous integration services for R package development. Tools for
Google Cloud Services and Microsoft Azure are also on the long-term
agenda.
I only checked paws and that has the ssm functionality according to the paws documentation about ssm. The cloudyr project has many aws packages on cran. Not sure if in one of them is the ssm functionality.
I want to develop an app using gracenote SDK and python, I see the python wrapper but I need to generate or make the _gnsdk.so for linux_x86-64, how I can do that ?
The python wrapper currently supports mac only, but will support linux in a future GNSDK release. There is no practical way for you to generate one, please check the Gracenote Developer website for future releases.
I'm trying to use the google-analytics framework to create predictive analysis tools. For example I would like to cluster my webpage visitors, etc.
In general, is there any list of machine learning algorithms implemented by this framework? for example: regression, clustering, classification, feature selection, etc.
Thank you for any help
Depending upon your language of choice, you might want to export your Google Analytics Metrics to flat files or a database and then start experimenting with ML models. Two popular languages with stable ML Implementations are Python and R. R's caret package includes tools for building a predictive model pipeline. Python's scikit-learn also contains implementations of all major classes of ML algorithms.
When you say GA framework I'll assume you're referring to the set of Google Analytics APIs listed here. The framework by itself doesn't provide machine learning capabilities. It merely provides access to the processed and aggregated GA data stored in Google's servers. You can use the API and feed the data to a machine learning application/system/program that does all of the stuff you mentioned.
I use ITK 4.3, VTK and Qt on Visual Studio 9. How do I add ITK-SNAP?
I want to know the difference between ITK and ITK-SNAP and what does ITK-SNAP add compared to ITK.
I started working with ITK. Do I need to change my code or can I continue in my project?
SNAP is a software application used to segment structures in 3D medical images. It provides semi-automatic segmentation using active contour methods, as well as manual delineation and image navigation. The software was designed with the audience of clinical and basic science researchers in mind, and emphasis has been placed on having a user-friendly interface and maintaining a limited feature set to prevent feature creep. ITK-SNAP is free software, provided under the General Public License. ITK-SNAP binaries are provided free of charge for academic or commercial use.
This tutorial provides a step by step walkthrough of building ITK-SNAP 2.4.0 from source on Windows. We will be using Microsoft Visual Studio 2010 for building the application. Make sure you have VS 2010 installed and VS Service Pack 1 as well. (if required) : Click Here for full tutorial
ITK is abbrevation of Insight Segmentation and Registration Toolkit which is open source library which provide image processing algorithms to develop your application on different platforms ex python, c++.You can follow this link: http://qtitkvtkhelp.blogspot.in/2012/11/itk-installation-for-msvc.html to build ITK and use that in your application. ITK-SNAP It is an open source software you can directly install it from here. I think this is solution for all of your questions.
We have a Cognos 8.x installation with hundreds of reports and dozens of models. We believe that many of the models are not currently in use on any reports and want to remove those models. Are there any tools that can be run against Cognos to list which reports are using which model?
Take a look at motioPI... its a 3rd party app built using the cognos sdk. You run it against one of your dispatchers and it proves quite handy for these tasks.
http://www.inmotio.com/investigator/home.do
not to mention its free.
There's an audit package that comes with Cognos installations that you can deploy to log user activity. This will help you understand usage and determine any unused models.
Under a normal installation it is located at c8_location/webcontent/samples/Models/Audit/Audit.cpf
With this package you can, amongst other things, list reports that are used, by package. All the while, you're also setting up an auditing tool.
You can refer to your Administration & Security guide to get information on how to setup and use this package.