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AH
Assistant Manager Data Literacy at K electric
Real User
Top 20
You don't need to be a programmer to adopt this solution but the modeling feature needs improvement

Pros and Cons

  • "Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills."
  • "A problem that I encountered was that I had to pay for the model that I wanted to deploy and use on Azure Machine Learning, but there wasn't any option that that model can be used in the designer."

What is most valuable?

Our organization employs people with diverse professional backgrounds. We have sociology, mathematics, and statistics backgrounds. We employ these people within our data science team. They require a certain amount of programming skills.

The good thing about Azure Machine Learning is they have a drag and drop feature. You can use Azure Machine Learning designer for all of your data science teams.

Any non-programmer can adopt it. All he needs is statistics and data analysis skills.                                                                                             

What needs improvement?

I used Azure Machine Learning in a free trial and I had a complete preview of the service. A problem that I encountered was that I had a model that I wanted to deploy and use on Azure Machine Learning, but there wasn't any option that that model can be used in the designer. I didn't find any option to upload my model, so that I can create my own block and use it in Azure Machine Learning designer.

I believe this is a problem because sometimes you have your model created on some other device and you just have a file that you think can be uploaded to Azure Machine Learning and can be tested through a simple drag and drop tool.

For how long have I used the solution?

We have been using Azure for three months. We have been exploring it for different use cases. 

What do I think about the stability of the solution?

I haven't used it long enough to have found any bugs in our current system. If there were bugs I would definitely report it on their website.

How was the initial setup?

We didn't have any problems with the setup. It was pretty straightforward.

What other advice do I have?

It's an easy tool. They have a good level of resources and we are pretty low with resources as far as data science is concerned.

Azure Machine Learning offers an opportunity for those who haven't been introduced to Azure programming. You can use the data analytics and their statistics skills to build and deploy data science solutions that can be beneficial for society and for different organizations.

I would rate it a seven out of ten.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Veronica Lambrechts
Senior Manager - Data & Analytics at a tech services company with 201-500 employees
Real User
Top 5
Easy to set up and the AutoML feature is helpful, albeit somewhat basic and should be enhanced

Pros and Cons

  • "The AutoML is helpful when you're starting to explore the problem that you're trying to solve."
  • "The AutoML feature is very basic and they should improve it by using a more robust algorithm."

What is our primary use case?

My primary use is for machine learning applications.

What is most valuable?

The AutoML is helpful when you're starting to explore the problem that you're trying to solve. It helps automate some of the applications of the algorithm.

What needs improvement?

The AutoML feature is very basic and they should improve it by using a more robust algorithm. It lacks deep learning type algorithms but works great for the basic classification and regression models.

For how long have I used the solution?

I have been using the Azure Machine Learning Studio on and off, or a few months. I have not used it consistently for a significant period of time.

What do I think about the stability of the solution?

From my experience over the past few months, I've found it to be pretty stable. I don't know how stable it would be if operationalized.

What do I think about the scalability of the solution?

From my experience, I think that it's scalable.

How are customer service and technical support?

Technical support is pretty good at answering questions, and the documentation is pretty clear to understand.

How was the initial setup?

Compared to their big competitor, it's much easier to set up.

What about the implementation team?

I work with a data architect who does the setup. I have not personally had to do it.

Which other solutions did I evaluate?

We are in the process of deciding which machine learning solution we want to use. I have been dabbling with Azure and we're deciding whether to implement it versus another cloud platform.

What other advice do I have?

I haven't done any research into what features they have on their roadmap.

Overall, I think that this is a comparable product.

I would rate this solution a seven out of ten.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Learn what your peers think about Microsoft Azure Machine Learning Studio. Get advice and tips from experienced pros sharing their opinions. Updated: November 2021.
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Omar AKIL
Big Data & Cloud Manager at a tech services company with 1,001-5,000 employees
Real User
Top 10
Stable and scalable with excellent technical support

Pros and Cons

  • "The solution is very fast and simple for a data science solution."
  • "The solution should be more customizable. There should be more algorithms."

What is our primary use case?

We primarily use the solution for data science.

What is most valuable?

The technical support of the solution is great. We have a contract with Microsoft and they are very good. 

The solution is very fast and simple for a data science solution. 

The pricing is very good.

What needs improvement?

The solution should be more customizable. There should be more algorithms. 

The solution needs more functionality.

For how long have I used the solution?

We're at the beginning of the process and have only been using the solution for a few months.

What do I think about the stability of the solution?

The solution is very stable. We haven't had issues with bugs or glitches. We haven't experienced any crashes.

What do I think about the scalability of the solution?

The solution is extremely scalable. This is because it's on the cloud. If a company needs to scale up they can do so quickly and easily.

At the moment, we have five employees using the solution. They are data scientists and engineers.

How are customer service and technical support?

The solution offers very good technical support. Microsoft is well represented here in France. We've been very satisfied with support so far.

Which solution did I use previously and why did I switch?

Previous to this solution, we had an improvised product. It wasn't a native cloud solution. We ended up choosing Azure Machine Learning because Azure is our management product. It made it easy for us to switch to the cloud.

How was the initial setup?

The initial setup was very easy because it's a cloud solution. With the cloud option, you just subscribe, and you are ready to go in a few minutes.

What other advice do I have?

I would recommend the product. It's a solution that can cover all the processes from data preparation to mobilization data while serving the clients and production. 

I'd rate the solution eight out of ten.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: My company has a business relationship with this vendor other than being a customer: partner
Saurabh-Singh
Head - Data Analytics at a consultancy with 51-200 employees
Real User
Top 10
Interface is well-organized and intuitive to use

Pros and Cons

  • "The interface is very intuitive."
  • "The data preparation capabilities need to be improved."

What is our primary use case?

We primarily use this solution for data analytics and model building.

What is most valuable?

The interface is very intuitive.

It is very well organized and the components can be utilized through drag-and-drop.

What needs improvement?

The data preparation capabilities need to be improved. Using this product, I can not prepare the data very much and this is a bottleneck in machine learning.

There are some features that are not supported, so I have to use either Python or R to accomplish these tasks.

For how long have I used the solution?

I have been working with the Azure Machine Learning Studio for between six and seven years.

What do I think about the stability of the solution?

Up to this point, we have not faced much in terms of issues with stability.

What do I think about the scalability of the solution?

Scalability-wise, we have not had to deal with any limitations. The only problem is that when certain options are not there, we have to use Python or R to handle those tasks.

How are customer service and technical support?

We have not faced any problems so I have not spoken with technical support.

How was the initial setup?

The initial setup is very straightforward. It is not difficult to do.

What other advice do I have?

I feel that this is a great solution. Even for people from the business side, this is a very good product. It is so intuitive that all of the information is there. The interface takes care of the most complex part, which has to do with the modeling. 

I would rate this solution a nine out of ten.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: I am a real user, and this review is based on my own experience and opinions.
GM
Director at a tech services company with 1,001-5,000 employees
Real User
Top 10
Easy to set up with good data normalization functionality

Pros and Cons

  • "The most valuable feature is data normalization."
  • "The data cleaning functionality is something that could be better and needs to be improved."

What is our primary use case?

Azure Machine Learning Studio works with our ERP solution.

What is most valuable?

The most valuable feature is data normalization.

What needs improvement?

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.

For how long have I used the solution?

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

What do I think about the stability of the solution?

This is a stable solution.

What do I think about the scalability of the solution?

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

How are customer service and technical support?

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

How was the initial setup?

The initial setup is straightforward and not too complex.

What about the implementation team?

We did the implementation by ourselves.

What's my experience with pricing, setup cost, and licensing?

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.

What other advice do I have?

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.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
LV
Advanced Analytics Lead at a pharma/biotech company with 1,001-5,000 employees
Real User
Top 5Leaderboard
Effective automation capabilities, easy to use, but infrastructure sharing across workspaces needed

Pros and Cons

  • "The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps."
  • "n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces."

What is our primary use case?

This solution can be used for data pre-processing, interactive data analysis, automated training, and pre-processing pipelines.

What is most valuable?

The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps.

What needs improvement?

In the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces. This would be something that would be helpful. Additionally, a better version for traceability functionality regarding data would be beneficial.

For how long have I used the solution?

I have been using this solution for approximately six months.

What do I think about the stability of the solution?

The solution is stable.

What do I think about the scalability of the solution?

I have found Microsoft Azure Machine Learning Studio scalable.

We have approximately eight people using the solution in my organization.

Which solution did I use previously and why did I switch?

I have previously used Databricks. We switched to this solution because it provides better automation capabilities, easier to use external code, and allows the use of other tools, such as Docker containers.

How was the initial setup?

The installation is easy. However, there is a bit more to do than with the installation of Databricks. The time it takes for the installation is approximately one day with a two-person team.

What about the implementation team?

We use one engineer for the implementation and maintenance of the solution.

What's my experience with pricing, setup cost, and licensing?

There is a license required for this solution.

What other advice do I have?

I would recommend this solution to others.

I rate Microsoft Azure Machine Learning Studio a seven out of ten.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Nhan Tran
Data & AI expert at One Mount Group
Real User
Top 5Leaderboard
A totally easy to use solution with highly accurate machine learning models

Pros and Cons

  • "I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model."
  • "I think they should improve two things. They should make their user interface more user-friendly. Integration could also be better. Because Microsoft Machine Learning is a Microsoft product, it's fully integrated with Microsoft Azure but not fully supported for other platforms like IBM or AWS or something else."

What is our primary use case?

I am using Microsoft Azure Machine Learning Studio for my personal use.

What is most valuable?

I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model.

What needs improvement?

I think they should improve two things. They should make their user interface more user-friendly. Integration could also be better. Because Microsoft Machine Learning is a Microsoft product, it's fully integrated with Microsoft Azure but not fully supported for other platforms like IBM or AWS or something else.

For how long have I used the solution?

I have been using Microsoft Azure Machine Learning Studio for almost two years.

What do I think about the stability of the solution?

Microsoft Azure Machine Learning Studio is a stable solution.

How was the initial setup?

The initial setup is straightforward. I think it's a cloud service, and whenever I create a new workspace, it takes me around five to ten minutes to deploy it.

What about the implementation team?

I implemented this solution.

What's my experience with pricing, setup cost, and licensing?

I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs.

What other advice do I have?

I would recommend this solution to new users. It's easy for people to use.

On a scale from one to ten, I would give Microsoft Azure Machine Learning Studio a nine.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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OD
Machine Learning Engineer at a tech services company with 1,001-5,000 employees
Reseller
Top 5Leaderboard
Advanced AutoML features, but the interface could be better

What is our primary use case?

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

What is most valuable?

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

What needs improvement?

The interface is a bit overloaded.

For how long have I used the solution?

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

What do I think about the scalability of the solution?

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

How are customer service and support?

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

How would you rate customer service and support?

Neutral

Which solution did I use previously and why did I switch?

also using Amazon and…

What is our primary use case?

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

What is most valuable?

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

What needs improvement?

The interface is a bit overloaded.

For how long have I used the solution?

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

What do I think about the scalability of the solution?

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

How are customer service and support?

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

How would you rate customer service and support?

Neutral

Which solution did I use previously and why did I switch?

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

How was the initial setup?

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

What other advice do I have?

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.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: My company has a business relationship with this vendor other than being a customer: Distributor
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