Microsoft Azure Machine Learning Studio Valuable Features

Software83c9
Software Engineer
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 easy drag and drop can create simple data science experiments. Low barrier to entry allows large number of candidates get started. The graphical nature of the output makes it very easy to create PowerPoint reports as well. View full review »
Danilo Faria
System Analyst at a financial services firm with 1,001-5,000 employees
* 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. * Easy to deploy and provide the project like a service. View full review »
Hameez Ariz
Process Analyst
* Split dataset * variety of algorithms * visualizing the data * drag and drop capability are the features I appreciate most. The capability to model the data by finding empty cells and filling missing values by deriving the median and more, are great features that makes the job way easier. View full review »
Find out what your peers are saying about Microsoft, Databricks, Knime and others in Data Science Platforms. Updated: October 2019.
378,570 professionals have used our research since 2012.
Nitin-Jain
Senior Associate - Data Science at a consultancy with 51-200 employees
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. View full review »
Rolf Lindgren
CEO at a recruiting/HR firm with 1-10 employees
Visualisation, and the possibility of sharing functions. View full review »
Find out what your peers are saying about Microsoft, Databricks, Knime and others in Data Science Platforms. Updated: October 2019.
378,570 professionals have used our research since 2012.
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