IBM Data Science Reviews - Page 13

Personally, I think that for a new user, it is a friendly way to work in a first phase with a treatment of certain information and then seek utility through the different statistical algorithms. Review collected by and hosted on G2.com.

I think that if you were using SSPS Statistics instead in the way of working from code to configurable addresses which is not necessarily bad, it could be a paradigm change that is difficult to overcome.

Another issue may be some very hidden configurations within the nodes. Review collected by and hosted on G2.com.

The UI is very clean which makes it easier to understand the product. Also, there are loads of documentation to learn more about how to use this tool for AI. Review collected by and hosted on G2.com.

I don't really know mainly because I only used it for a hackathon and not for a company. There was nothing I disliked. Review collected by and hosted on G2.com.

When I was using Watson Studio, it was fairly well integrated w/ Watson Cloud, allowing one to spin up infrastructure to connect to your analytics assets built with Watson Studio. This was good Review collected by and hosted on G2.com.

This is basically SPSS Modeler, but in the cloud. It suffers from the same issues Modeler suffered from a data-science/ML dev perspective, little ability to customize elements of your model stack, clunky integration w/ custom outside code (R or Python). Review collected by and hosted on G2.com.

I liked very useful examples and algorithms and Data provided. Easy to get started Review collected by and hosted on G2.com.

It doesn't easily integrate with outside Data especially when the Data has to remain secure/private Review collected by and hosted on G2.com.

You barely need any knowledge of coding to be able to use SPSS Modeler. Just with a little bit of know-how of things, you can already start building prediction and segmentation models. It's super light-weight so most of the models you can run on the laptop instead of having to deploy them on a server. Drag and drop interface, and connecting together the data flow is amazing. Review collected by and hosted on G2.com.

Deploying a stream on a SPSS server is not that straight-forward Review collected by and hosted on G2.com.

It's easy for beginners to use, most of the functions are in the dropdown menu. Review collected by and hosted on G2.com.

The syntax function of SPSS is very inconvenient. If you are an intermediate data analyst, switch to other softwares, e.g., R, Stata. Review collected by and hosted on G2.com.

I am a fan of the extensive APIs that Watson STT provides for transcription. We have also used them heavily for training the language models.

The APIs allow us to connect Watson to our Video cloud services - and make the process seamless. We have created an end to end Closed captioning platform based off Watson STT , the APIs and integrations with our video cloud.

This solves a big need for us. Review collected by and hosted on G2.com.

I'd like the language models to be improved periodically.

For an education company such as ours, the ability to generate high accuracy transcripts right off the bat are a huge difference maker. Review collected by and hosted on G2.com.

Easy to install / upgrade / maintain

Intuitive GUI for the newbie to begin using the studio

Integration with Spark

Asset and community access Review collected by and hosted on G2.com.

The videos in the tutorials are all on Youtbe which are usually blocked on most of work campuses.

Cannot be embedded into mobile apps except CoreML in iOS app.

Since the features are changing continuously, some of the tutorials don't fit the current version. Review collected by and hosted on G2.com.

As a result of our work, we process our raw and raw information that we obtain with this application and make it reportable. The application is one of the best applications in my opinion. The data processing speed is very good, the interface it uses is very good. Reporting screen is working healthy.

Healthy analyzes and reporting of these analyzes work very well. The real purpose of this program already. I am very pleased. Review collected by and hosted on G2.com.

I had no bad process during use and installation. Review collected by and hosted on G2.com.

Modeler is great when yu have multiple problems that can be resolved with analytics. You can use it to modify data in order to be in good condition for modeling and also it have a significant ammount of techniques that you can apply. Also, you can integrate Modeler with R project and with Phyton, wich is great to give it more functions.

One great advantage of modeler is the easy of automatization of process. Review collected by and hosted on G2.com.

Modeler lacks of important statistical tests, like normality, randomness, etc. This is not good when you are making regressions and need to test the assumtions about the errors.

Other thing that migth be a need to improve is the lack of techniques to analyze unestructured data like images or videos. Review collected by and hosted on G2.com.