What do you like best?
Azure Machine Learning platform is aimed at setting a powerful playground both for newcomers and experienced data scientists. It is more more flexible in terms of out-of-the-box algorithms when compared with other platforms. A big part of Azure ML is Cortana Intelligence Gallery. It’s a collection of machine learning solutions provided by the community to be explored and reused by data scientists. It is a powerful tool for starting with machine learning and introducing its capabilities to new employees. On the other hand, Azure ML supports graphical interface to visualize each step within the workflow. Perhaps the main benefit of using Azure is the variety of algorithms available to play with. It supports around 100 methods that address classification (binary+multiclass), anomaly detection, regression, recommendation, and text analysis. It also has one clustering algorithm (K-means). Once can execute the 'R ' scripts within the platform to meet his or her needs.
What do you dislike?
Going towards machine learning with this platform has some learning curve. It is a it more expensive than the Amazon platform. Sometimes the speed of execution can be slow.
Recommendations to others considering the product
It is one of the most user friendly cloud hosting platforms and integrates well with other MIcrosoft products.
What business problems are you solving with the product? What benefits have you realized?
It has helped me in easy drag-and-drop of objects on the interfaces to create models that can be pushed to the web as services to be utilized by tools like business intelligence systems.