Microsoft Azure Machine Learning Studio Other Advice

Alexandre Akrour
CEO at Inosense
Microsoft has increased the usability and the features since we first implemented this solution. If I had to start this process over again, I would involve Microsoft earlier because they were great for providing support, as well as guidance on the architecture and what kind of stuff you can do with the tool, and what you should do with it. This was very helpful to orient the team to the right documentation and tutorials. The second thing I would do is to start working with DevOps activity as soon as you can. We found ourselves redoing the same things many times, instead of having a DevOps pipeline to implement the stuff that we already stabilized, for example, and then not losing time. The third thing is involving an integrator to help put together the big picture. I would rate this solution a seven out of ten. View full review »
Software83c9
Software Engineer
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 barrier to entry. If one is not a programmer or statistician, MLS is a good way to get a project started, create a proof of concept. View full review »
ChrisPeddie
Tech Lead at a tech services company with 1,001-5,000 employees
My advice to anybody who is implementing this solution is to be prepared to take a slow approach to get the best results. The biggest lesson that I have learned from using this solution is that the strategic outsourcing contact will need to have a strategy for the next three to five years because the efficiencies that we will be gaining from AI will reduce the requirements on physical staff doing traditional roles. However, the support element will increase. It means that the roles will change and evolve over the next three to five years within the UK contact center based on the deployment of AI. I think that we probably didn't start from the point that would have benefited us most in terms of the AI. Had we put more research into the front end then there would have been a lot less work during the implementation. I would rate this solution a six out of ten. View full review »
Find out what your peers are saying about Microsoft, Databricks, Knime and others in Data Science Platforms. Updated: November 2019.
383,162 professionals have used our research since 2012.
Danilo Faria
System Analyst at a financial services firm with 1,001-5,000 employees
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. View full review »
Find out what your peers are saying about Microsoft, Databricks, Knime and others in Data Science Platforms. Updated: November 2019.
383,162 professionals have used our research since 2012.
Sign Up with Email