Microsoft's Azure Machine Learning is and end-to-end data science and analytics solution that helps professional data scientists to prepare data, develop experiments, and deploy models in the cloud. It replaces the Azure Machine Learning Workbench.
$0
per month
Dragon Speech Recognition
Score 8.1 out of 10
N/A
Nuance's Dragon Speech Recognition suite are applications for lawyers, medical practitioners, and other professionals, allowing them to dictate and record notes (according to the vendor) faster than typing, accurately.
My job requires that I produce lengthy and detailed minutes of meetings and Nuance Dragon Speech Recognition is absolutely ideally suited for this purpose. Notably, meetings are recorded and it is extremely easy to playback the recording of meetings while dictating notes. This is a remarkable saving in time and effort in producing minutes that might otherwise take a few days. I cannot think of any scenario where it would be less appropriate to use Nuance Dragon Speech Recognition other than in a situation where it is not possible to dictate for whatever reason.
User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.
Overall, its gives the functionality that I need in my role and can support with automating tasks. I mainly use it for autotext, to add blocks of text and it works universally across all applications. It saves time and works well in Windows 11. It works very well navigating the web.
It is easier to learn, it has a very cost effective license for use, it has native build and created for Azure cloud services, and that makes it perfect when compared against the alternatives. As a Microsoft tool, it has been built to contain many visual features and improved usability even for non-specialist users.
Other than the more recent speech recognition tools from Microsoft, Google, etc., I have always used Nuance Dragon Speech Recognition. I was introduced to AI technology on an appraisal assignment. During the engagement, I had an opportunity to learn about the technology, and when I researched speech recognition software, the best reviews were of Nuance Dragon Speech Recognition. I purchased Nuance Dragon Speech Recognition and have stayed with the product.
Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster;
Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat.
Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details
