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Bottom Line
Watson is an umbrella for all IBM deep learning and artificial intelligence, as well as machine learning. The company was a pioneer in introducing AI technologies to the business world. What this means for buyers: Watson Studio is a top contender for any organization looking to deploy machine learning and deep learning technologies.
The platform provides extensive tools and technologies for data scientists, developers and subject matter experts that desire to explore data, build models, and train and deploy machine learning models at scale. The solution includes tools to share visualizations and results with others. Watson Studio supports cloud, desktop and local deployment frameworks.
The latter resides behind an organization’s firewall or as a SaaS solution running in an IBM private cloud. IBM Watson Studio is ranked as a “Leader” in the Forrester Wave. It was a Customers’ Choice 2018 recipient at Gartner Peer Insights.
Product Description
Watson Studio relies on a collection of IBM tools and technologies to build powerful machine learning applications and services. This includes IBM Cloud pretrained machine learning models such as Visual Recognition, Watson Natural Language Classifier, and others. The environment uses Jupyter Notebooks along with other open source tools and scripting languages to complement built-in collaborative project features.
The result is an environment that facilitates fast and powerful machine learning development and fine tuning of models. Data scientists and others can choose from various capacities of Anaconda, Spark and GPU environments.
Watson Studio supports enhanced visual modeling through a drag-and-drop interface provided by IBM’s SPSS Modeler. In addition, it accommodates automated deep learning using a drag-and-drop, no-code interface in Neural Network Modeler.
Overview and Features
User Base
Data scientists, developers and subject matter experts.
Interface
Graphical drag-and-drop and command line.
Scripting Languages/Formats Supported
Supports Anaconda and Apache Spark. The latter offers Scala, Python and R interfaces.
Formats Supported
Most major data and file formats are supported through open source Jupyter Notebooks.
Integration
IBM Watson Studio connects several IBM products, including SPSS Modeler and Data Science Experience (DSX) along with open source tools, in order to deliver a robust Predictive Analytics and Machine Learning (PAML) solution.
The environment accommodates open data sets through Jupyter Notebooks, Apache Spark and the Python Pixiedust library. The cloud version features interactivity with Notebook servers and R Studio, along with Python, R., and Scala coder for data scientists.
Reporting and Visualization
Visualization through SPSS Modeler. Strong logging and reporting functions are built into the product.
Pricing
IBM has adopted a pay-as-you-go model. Watson Studio Cloud – Standard costs $99 per month with 50 capacity unit hours per month included. Watson Studio Cloud – Enterprise runs $6,000 per month with 5,000 capacity unit hours. Watson Studio Desktop costs $199 per month with unlimited modeling. Watson Studio Local – for enterprise data science teams N/A.
IBM Watson Studio Overview and Features at a Glance:
| Vendor and features | IBM Watson Studio |
|---|---|
| ML Focus | Broad data science focus with cloud and desktop ML platforms. |
| Key Features and capabilities | Strong visual recognition and natural classification tools. Flexible approach that incorporates open source tools. Connects to IBM SPSS Modeler. |
| User comments | Highly rated for features and capabilities. Some complaints revolving around using notebooks. |
| Pricing and licensing | Tiered model from $99 per month per user to $6,000 per month per user or more at enterprise level. |
