Microsoft Azure Machine Learning Studio Review

User-friendly, no code development, and good pricing but they should offer an on-premises version


What is our primary use case?

We plan to use this solution for everything in business analytics including data harmonization, text analytics, marketing, credit scoring, risk analytics, and portfolio management.

How has it helped my organization?

It allows us to do machine learning experiments quickly.

We did not have machine learning solutions or platform earlier.

What is most valuable?

It's user-friendly, and it's a no-code model development. It's good for citizen data scientists, but also, other people can use Python, R or .NET code.

If you are on Microsoft Cloud, the development and implementation are super easy.

What needs improvement?

Every tool requires some improvement. They have already improved many things. They had added new features and a new pipeline.

They should have an on-premise version, other than Python and R Studio, which is only good for cloud-based deployments.

If they could have a copy of the on-premise version on Mac or Linux or Windows, it would be helpful.

It should have the flexibility to work o the desktop. They should have a desktop version to work on the platform.

For how long have I used the solution?

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

What do I think about the stability of the solution?

It's a stable solution. Microsoft is very stable in general.

What do I think about the scalability of the solution?

It's very scalable because it is using Microsoft cloud compute power.

We want to extend organization-wide, but currently, we are only working on a use case basis.

How are customer service and technical support?

We have not required help from technical support, but Microsoft technical support comes with it when you subscribe.

How was the initial setup?

Deployment of the tool is simple. Just one click on Microsoft. Once you have procured the license, you can just log in and use it. It's a ready-to-use tool.

When you deploy the solution after analytic development, it depends on the project but it can take anywhere from one month to six months.

Also, depending on the infrastructure, the initial deployment can take one week to a month.

What about the implementation team?

In-house expertise.

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

The licensing cost is very cheap. It's less than $50 a month would costs for multiple users.

What other advice do I have?

If you want to build a solution quickly without knowing any coding, it's pretty good to start with.

I will take a week to learn, from my experience. For anyone who is interested in trying it, they should start with the free version, which is free for up to 10 gigabytes of workspace.

Just log in and start developing and exploring the tool before onboarding.

I would rate Microsoft Azure Machine Learning 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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