Microsoft Azure Machine Learning Studio Reviews

We're setting up the environment for our data science and IT project. It is a protected environment for protected data. So, there's a lot of architecturing in this solution.

Their support is helpful.

It is not easy. It is a complex solution. It takes some time to get exposed to all the concepts. We're trying to have a CI/CD pipeline to deploy a machine learning model using negative actions. It was not easy. The components that we're using might have something to do with this.

I don't know about its stability yet. We're facing some issues, and we are approaching the product team for help. It might also have something to do with our environment setup. Our environment is inside V-Net, and we have a lot of security requirements.

We're working with their team to resolve the issues. Having someone to assist you makes it easier. We have someone at Microsoft to help us with it. They're very helpful.

I have worked a little bit with Open Source.

We are only testing, and we have to be very careful of the restrictions. I'm a little bit aware of the issues about ML Ops, and I am trying to see if Azure Machine Learning Studio can address those issues. For now, I would rate it a seven out of 10. I have to explore it more.

Azure Machine Learning Studio works with our ERP solution.

The most valuable feature is data normalization.

The data cleaning functionality is something that could be better and needs to be improved.

There should be special pricing for developers so that they can learn this solution without paying full price.

I have been using Azure Machine Learning Studio for more than two years.

This is a stable solution.

I believe that it is scalable. At this time, we have not more than ten users. These include programmers, as well.

I have been in contact with technical support and they are good. I am happy with their response time.

The initial setup is straightforward and not too complex.

We did the implementation by ourselves.

From a developer's perspective, I find the price of this solution high. If somebody wants to learn how to use this platform then they have to spend money doing it. I know people who are interested in learning it but do not want to pay the full cost.

Microsoft Azure Machine Learning Studio is a good solution that would recommend to others, but I would like to see more support and more information available for developers.

I would rate this solution an eight out of ten.

My primary use case is for supervised and unsupervised learning models.

The most valuable feature is its compatibility with Tensorflow.

In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data.

I've been using this solution for a year.

The stability is questionable, given that Microsoft will be retiring the classic version of this product in 2024, and it's unclear how this will affect projects created on the classic version.

This solution is scalable.

The initial setup was straightforward, though you do need some experience with Azure administration in order to install it.

I evaluated Amazon SageMaker, which is a bit more advanced than Azure Machine Learning, with more functionalities and only a slightly higher price.

I would rate this solution as seven out of ten.

I have used it to deploy predictive models in the healthcare sector.

It has helped in reducing the time involved for coding using R and/or Python. Also, web service is quite easy and convenient to use for clients. 

Its ability to publish a predictive model as a web based solution and integrate R and Python codes are amazing. It helps in building customized models, which are easy for clients to use.

It could use to add some more features in data transformation, time series and the text analytics section. Microsoft should also include more examples and tutorials for using this product.

We initially moved to this solution because our company needed to complete a system upgrade. We had to move the Db2 data to a AS400 system. 

Their web interface is good but the on-prem site interface is outdated. This solution could be improved if they could integrate the data pipeline scheduling part for their interface. When we are scheduling, they provide only one exclusion per day in the initial scheduling. We then have to configure it through the Linux front jobs if we want a high value job. It would help us and our customers if this was possible from the initial interface itself.

I have been using this solution for a few months. 

This is a stable solution. 

We have had limited engagement with the customer support team but when we have needed their help, they were helpful. 

Positive

The infrastructure and the software configuration part was done by one of my teammates. It was completed in two working days. We did experience some issues with the board communications which extended the time to complete the setup. This was only for the DataStage installation which is one of many components of this solution.

I would advise others to identify the communication between servers and the client tools correctly as well as the user allocation for those. If you are working from a client environment and connecting to the server, it is important that the configuration is done correctly.

I would rate this solution an eight out of ten. 

I use the solution for learning purposes for the most part.

Personally, I got interested in data science and machine learning due to using this product. After some time with it, these topics didn't intimidate me.

The solution is very easy to use. It's user-friendly and simple to navigate.

The initial setup is very simple and straightforward.

The solution is quite stable.

It's the first software that I've used in terms of machine learning. Therefore, I don't have anything to compare it to, however, it was okay for me. I didn't have any problems or anything.

Maybe it can be integrated with something else. For example, business analytics. That way, you could also give creative reports. It's possible it could be integrated with the Power BI, as it's also Microsoft. That said, I'm not really sure. It if isn't possible, it's something they could consider for a future release.

Microsoft needs to be sure to monitor the security and ensure they are constantly updating it.

It would be nice if the product offered more accessibility in general.

I've only been using the solution for a short amount of time. It's just for a course at school.

The solution is stable. I didn't have any lags or anything. It was smooth. There are no bugs or glitches. I don't recall it crashing or freezing on me.

The solution seems to be able to work well for companies both large and small. However, I did not personally attempt to scale it.

I never really dealt with technical support directly. I have my teacher to teach or to ask questions to. He would often recommend these online tutorials to learn about the solution as well. I never really thought of asking a chat box, for example, of Microsoft, where I could type any help. I never really considered it. Therefore, I can't speak to how helpful or responsive they typically are.

I did not use a different solution. This is the first solution I used for machine learning.

The initial setup was not difficult or overly complex. It's very straightforward, very simple, and very easy to understand. 

Everything is just written down in a way that was an easy way to understand, even for someone who isn't used to the packages of Microsoft.

I handled the deployment myself. I did not need the help of a consultant or integrator.

I'm just a student. I was learning about machine learning via this product.

I'm not sure which deployment model we are using.

I would rate the solution at an eight out of ten.

I would advise other potential users to just start using it. If they really want to learn it, it will take a bit of time. Even though it's easy to use, you need some knowledge in data science. That will help make the process easier.

Exploration of connections between biodata and psychometric test results.

Visualisation, and the possibility of sharing functions.

Operability with R could be improved.

in-house translation, time series and computer vision applications;  create models from scratch and just play around with data visualization.

Azure's AutoML feature is probably better than the competition.

The interface is a bit overloaded.

I've been using Azure ML Studio for about three months. 

Azure ML Studio has the same scalability as other similar solutions.

I haven't used Microsoft Azure support for this so far.

also using Amazon and Google solutions. In terms of performance, I think they're pretty much the same. Amazon SageMaker is a bit more mature.  Google Colaboratory and Vertex AI have better UI

Setting up ML Studio is very straightforward because it's a cloud thing. 

I rate Microsoft Azure Machine Learning Studio seven out of 10. I would definitely recommend it to customers. The autoML, in particular, has some very advanced features.