Microsoft Azure Machine Learning Studio Overview

Microsoft Azure Machine Learning Studio is the #1 ranked solution in our list of top AI Development Platforms. It is most often compared to Databricks: Microsoft Azure Machine Learning Studio vs Databricks

What is Microsoft Azure Machine Learning Studio?

Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.

It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.

Microsoft Azure Machine Learning Studio is also known as Azure Machine Learning, MS Azure Machine Learning Studio, MS Azure Machine Learning Studio, MS Azure Machine Learning Studio.

Microsoft Azure Machine Learning Studio Buyer's Guide

Download the Microsoft Azure Machine Learning Studio Buyer's Guide including reviews and more. Updated: May 2021

Microsoft Azure Machine Learning Studio Customers

Walgreens Boots Alliance, Schneider Electric, BP

Microsoft Azure Machine Learning Studio Video

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CEO at a recruiting/HR firm with 1-10 employees
Real User
Visualizations are a key feature but it needs better operability with R

What is our primary use case?

Exploration of connections between biodata and psychometric test results.

What is most valuable?

Visualisation, and the possibility of sharing functions.

What needs improvement?

Operability with R could be improved.

For how long have I used the solution?

Less than one year.
System Analyst at a financial services firm with 1,001-5,000 employees
Real User
Easy to deploy, drag and drop makes it easy to test various algorithms

What is our primary use case?

The first time that I used this tool was in a project related to bike usage in the city of Boston. This project was part of a course that I concluded some months ago. In this project I used components to read data, for exploratory analysis, for steps of data munging, to split data, select hyperparameters, and some machine learning algorithms. In some steps I needed to insert R modules to apply some data transformation. The target of this exercise was to predict bike usage in a day.

Pros and Cons

  • "It is very easy to test different kinds of machine-learning algorithms with different parameters. You choose the algorithm, drag and drop to the workspace, and plug the dataset into this component."
  • "When you import the dataset you can see the data distribution easily with graphics and statistical measures."
  • "I would like to see modules to handle Deep Learning frameworks."

What other advice do I have?

You will be able to create your machine-learning project and extract insights from it just by dragging and dropping components and adjusting some parameters. This tool is very user-friendly, so without a lot of programming skills you can build machine-learning projects. If you need more control over machine-learning modules you will need to add R or Python modules to create a customized machine-learning model.
Learn what your peers think about Microsoft Azure Machine Learning Studio. Get advice and tips from experienced pros sharing their opinions. Updated: May 2021.
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Process Analyst
Real User
Split dataset, data visualization are helpful, but it needs integrated Pivot Table feature

What is our primary use case?

My primary use of ML Studio is to experiment with different algorithms and learn the techniques of machine learning. In the meantime, I have developed a few models related to finance. One of the predictive models I designed was an Invoice Discrepancy Prediction model using a Multiclass Neural Network algorithm. This model predicts if an invoice will have a variance of some sort when checked against the purchase order, before the payments are to be processed.

Pros and Cons

  • "Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
  • "I personally would prefer if data could be tunneled to my model through a SAP ERP system, and have features of Excel, such as Pivot Tables, integrated."
Software Engineer
Real User
Enables quick creation of models for PoC in predictive analysis, but needs better ensemble modeling

What is our primary use case?

To create quick data analytic experiments, without incurring the time and cost of spinning up servers, setting up Hadoop, etc. Although MLS makes it very easy to deploy the resulting machine-learning models via REST API, I primarily use MLS as a means to quickly spin up experiments and create proof of concept models.

Pros and Cons

  • "MLS allows me to set up data experiments by running through various regression and other machine learning algorithms, with different data cleaning and treatment tools. All of this can be achieved via drag and drop, and a few clicks of the mouse."
  • "The graphical nature of the output makes it very easy to create PowerPoint reports as well."
  • "Scalability, in terms of running experiments concurrently is good. At max, I was able to run three different experiments concurrently."
  • "Enable creating ensemble models easier, adding more machine learning algorithms."

What other advice do I have?

For data science professionals or programmers I would rate this solution a four out of 10. A major feature is missing: creating ensemble models. This can be achieved with the tool, but it's clumsy and slow. For marketing or business professionals I would rate it an eight out of 10. It has a low barrier to entry, and can quickly create models that can be used for proof of concept and justify further investment in a full data science or Big Data project. R and Python, in my mind, are still the way to go for a true data science/predictive analysis project. MLS's value is the ease of use and low…
Senior Associate - Data Science at a consultancy with 51-200 employees
Real User
Leaderboard
​It has helped in reducing the time involved for coding using R and/or Python

What is our primary use case?

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

Pros and Cons

  • "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 has helped in reducing the time involved for coding using R and/or Python."
  • "​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.​"
Co-Founder at a tech services company with 51-200 employees
Real User
Top 20
Simplified development as scripts can be designed and implemented in real time

What other advice do I have?

For the best, reliable results, it is the best solution to have in mind. Try it out.
Buyer's Guide
Download our free Microsoft Azure Machine Learning Studio Report and get advice and tips from experienced pros sharing their opinions.