Overview
What is IBM Watson Studio?
IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data…
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What is IBM Watson Studio?
IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.
IBM Watson Studio Competitors
IBM Watson Studio Technical Details
Operating Systems | Unspecified |
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Mobile Application | No |
Frequently Asked Questions
Amazon SageMaker and Azure Machine Learning are common alternatives for IBM Watson Studio.
Reviewers rate Automatic Data Format Detection and Visualization and Interactive Data Analysis highest, with a score of 10.
The most common users of IBM Watson Studio are from Enterprises (1,001+ employees).
Comparisons
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Reviews From Top Reviewers
(1-5 of 54)
Rating: 9 out of 10
May 10, 2021
KB
Vetted Review
Verified User
2 years of experience
Google Cloud may be a good place but it is not as easy to understand as IBM Watson is. Google Cloud has a lot of things and it is terrifying for a beginner. You need hours of specialization for that. On other hand, anyone can start using IBM Waston just by the following documentation.
IBM Watson Studio on Cloud Pak for Data Review
Rating: 7 out of 10
March 30, 2021
LR
Vetted Review
Verified User
1 year of experience
AWS Sagemaker is a well-established product that supports on-demand notebooks, data pipelines, and so on, however, it also comes with the learning overhead of the whole AWS stack. It does allow per-defined models, but the benefit of using IBM Watson Studio is that users are able to leverage per-trained models and significantly reduce training time.
Auto AI is a must have for every Data Analyst
Rating: 10 out of 10
January 13, 2021
JR
Vetted Review
Verified User
1 year of experience
Easy to use, but still requires a lot of coding to use. There is no ranking of models used and models are not persistent, which means you have to keep running the models again every time you leave the session. The filesystem is clunky and need to keep authorizing Google Drive to save any datasets.
Data scientist - as a beginner
Rating: 8 out of 10
December 18, 2020
NS
Vetted Review
Verified User
IBM offers a deep neural network training workflow, with a flow editor interface similar to the one used in Azure ML Studio. However, the custom build modeling in IBM has notebooks such as Jupiter to program models manually using popular frameworks like TensorFlow, sci-kit-learn, PyTorch, XGboost, PMML, and IBM SPSS.
My first experience on Watson Studios
Rating: 9 out of 10
November 24, 2020
MW
Vetted Review
Verified User
With my experience on Jupyter Notebook I think both are good and currently more comfortable with Watson Studio product. With Jupyter it's open source (free) is always good. "Lots of languages (50), data visualization with Seaborn, work with the building blocks in a flexible and integrated manner • modern JavaScript development: npm-based packaging, typescript, phosphor.js, • clean model/view separation, • well separated public/private APIs, fully extensible by third parties, high performance and Design."