Azure Machine Learning vs. expert.ai NL Suite

For [a] data scientist require[d] to build a machine learning model, so he/she didn't worry about infrastructure to maintain it.

All kind of feature[s] such as train, build, deploy and monitor the machine learning model available in a single suite.

If someone has [their] own environment for ML studio, so there [it would] not [be] useful for them.

Existing body of data regarding our demographic targets, including social media, so for our psychographic targets, quite helpful. Alerts assist us in anticipating specific market demands. Yet AI is in its infancy so Cogito can only go as far as beta can go.

Incentivized

• 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.

Incentivized

• Humongous amounts of data can be found
• Autonomous
• Gives us actionable data and market insights and ideas

Incentivized

• It would be great to have text tips that could ease new users to the platform, especially if an error shows up
• Scenario-based documentation
• Pre-processing of modules that had been previously run. Sometimes they need to be re-run for no apparent reason

Incentivized

• 500k bits of data is a lot.
• Visualization is good but there is room for more refinement.
• Harnesses AI, yet more potential there.

Incentivized

Easy and fastest way to develop, test, deploy and monitor the machine learning model.

- Easy to load the data set

-Drag and drop the process of the Machine learning life cycle.

Fast with just a few clicks and quite breathtaking what it finds. Beware you cannot search, only find!

Incentivized

Support is nonexistent. It's very frustrating to try and find someone to actually talk to. The robot chatbots are just not well trained.

Incentivized

Not sure

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.

Incentivized

We were primitive using Salesforce, and while it is great, Cogito is a laser.

Incentivized

• 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

Incentivized

• Identified new psychographic and demographic targets.
• Kept us in the tide of social media as it breaks.
• Improved our bottom line at least 7% so far.

Incentivized