Likelihood to Recommend 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.
Read full review IBM Watson Machine Learning is an AI-based scalable self-learning model for any type of business. It can be used to help any company automate repetitive tasks, predict future trends, and make data-driven decisions. I used it to predict stock prices based on certain variables. It works well, cost me nothing, and gives me the ability to create my own AI-based models that I can use for any purpose.
Bed Raj CITO (Chief Information Technology Officer)
Read full review Pros 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. Read full review Good machine learning tool Easy integration Read full review Cons 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 Read full review Proper usage of REST API documentation is missing. Not localization friendly, cannot support regional or local language documents. Bed Raj CITO (Chief Information Technology Officer)
Read full review Usability 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.
Read full review Support Rating Support is nonexistent. It's very frustrating to try and find someone to actually talk to. The robot chatbots are just not well trained.
Read full review IBM had a hard time providing business level support. There were a lot of data scientists and technology experts but rarely a simple business person shows up. Also the way IBM operates IBM Consulting has competing priorities as compared to IBM Technology. This has resulted in a lot of confusion at the client's end.
Read full review Implementation Rating Not sure
Read full review Alternatives Considered 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.
Read full review We have been using Microsoft Azure as a machine learning tool. But the challenges remain the same. These are all tools that you need a robust analysis before a decision on the tool. Unfortunately, the technology company cannot make that determination due to lack of core business understanding. Without that the project is doomed.
Read full review Return on Investment 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 Read full review Create secure business environment. Save upto 90% of manual labor. Improve my sales and marketing ROI. Bed Raj CITO (Chief Information Technology Officer)
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