Azure Machine Learning Studio Reviews

16 Ratings
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Score 6.8 out of 100

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Reviews (1-3 of 3)

Anonymous | TrustRadius Reviewer
August 23, 2019

Azure Machine Learning studio is not ready for serious production use

Score 2 out of 10
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I create data science learning materials on Azure that require no coding. I use publicly available property data from Hong Kong island and surrounding areas. I teach my students how to preprocess the data, clean it up and create a hypothesis based on the type of data. We apply learning algorithms on the data and improve on the mode. The dataset was relatively small yet it took a while for the platform to get the analysis.
  • Adding python scripts
  • Pre-trained models
  • Case studies of industry projects
  • It would be great to have text tips that could ease new users to the platform, especially if an error shows up
  • Scenario-based documentation
  • Pre-processing of modules that had been previously run. Sometimes they need to be re-run for no apparent reason
Azure can be a more unified product. It feels like 10 different tech teams were building it but we're not talking to each other. An example is when the user needs to know what is the next step. Automatically saving a previous state is very helpful as new users are usually not aware of the functionality.
Support is nonexistent. It's very frustrating to try and find someone to actually talk to. The robot chatbots are just not well trained.
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Anonymous | TrustRadius Reviewer
May 13, 2019

Machine learning tool that is easy to learn and use

Score 9 out of 10
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Currently, it is used for our information technology sector to implement machine learning features in-house. The idea is to explore models and perform some experimentation. It's used to find Machine Learning solutions for internal use in the company. The Microsoft resources in this tool make it easier to use machine learning, like the use of visual interfaces and how they manage deployment.
  • Visual interface
  • Possibility to track the IDs and also get the results from it
  • Charts to collect data and quickly check for performance/problems
  • Hard to apply Python code and run
  • More models could be available
  • Tableau interface would be perfect
It is good to quickly and easily deploy a model for Machine Learning. It has a few coding aspects that enable machine learning that at first sight can be a problem for non-machine learning specialists. The system tries to gets the easiest results as possible.

It is less appropriate for complex systems and for detailed results to be analyzed.
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Gabriel Chiararia | TrustRadius Reviewer
May 21, 2018

Azure ML: Most user friendly and the cheapest!

Score 10 out of 10
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I was the president of an MBA class that used Azure ML to run analytics models. The tool was used by 40 students. We analyzed a few datasets to understand the tools, and afterward, we were able to create a few analytics products based on Azure ML.
  • User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
  • Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
  • Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
  • Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
  • Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.
  • Few models: Even though it has a lot of Machine Learning models, it is quite limited when compared to R. Most Data Scientists still use and prefer R, so the newest models tend to release as R libraries. With Azure ML, we need to wait for Microsoft to evaluate and decide if including a new model is a good idea or not
  • Tableau interface: last time I checked there was no easy way to connect with Tableau.
  • Cloud based: You always need a good internet connection to use it.
Well suited:
- Run a machine learning model the fastest and easiest way;
- Working with an organization with no coding background;
- Trying to get the most of data the cheapest and easiest way possible;
- Introducing analytics and machine learning concepts to an organization or class;

Less appropriate:
- Running complex Machine Learning models;
- Visualizing data more deeply;
- Running new analytics models;
- Running heavy statistical models;
Read Gabriel Chiararia's full review

About Azure Machine Learning Studio

Microsoft's Azure Machine Learning Studio is and end-to-end data science and analytics solution that helps professional data scientists to prepare data, develop experiments, and deploy models in the cloud. It replaces the Azure Machine Learning Workbench.
Categories:  Machine Learning

Azure Machine Learning Studio Technical Details

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Mobile Application:No