Forrester ranks IBM Watson Studio as the leader
The new Forrester Wave Report examines Predictive Analytics & Machine Learning Platforms
IBM Watson Studio
Accelerate the machine and deep learning workflows required to infuse AI into your business
IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.
Benefits
Flexible Tools
Flexible platform allows you to access the broadest range of data science tools, from data prep to model development, for coders and non-coders.
Hybrid Environment
Multi-cloud environment allows you to bring your analytics to the data; on-prem, in IBM Cloud Private, or in the public cloud to achieve greater data access and agility.
Production Ready
Ability to deploy, evaluate and manage models with ease in a secure environment, so you can put data science into production faster.
Watson Studio details
Embedded Watson tools
Train Watson with embedded AI services, including Watson Visual Recognition and Natural Language Classifier. Customize your models and deploy them as APIs with Watson Machine Learning, or CoreML.
Built on open source
Use familiar open source data science and machine learning tools, with Jupyter Notebooks with Anaconda and RStudio. Access the most popular libraries or bring your own.
Intuitive visual modeling
No-code visual modeling with Neural Network Modeler for designing neural architectures using the most popular deep learning frameworks. Train models easily with SPSS.
Easier data preparation
Interactively discover, cleanse, and transform your data with Watson Knowledge Catalog. Understand the quality and distribution of your data with built-in charts and statistics.
Interactive dashboards
Explore data and share compelling visualized results through interactive dashboards created within a powerful drag-and-drop authoring environment.
Elastic compute options
Easily scale your compute resources and customize your package dependencies to create a custom and reproducible environment that can be shared across your organization.
Your data, your choice. Build and deploy your models where you want.
Customer success stories
Product Offering Images
Uncover hidden insights from data with built-in data cleaning and transformations with Data Refinery
Compare runs and conduct model hyper-parameter optimization easily with Deep Learning Experiments
Work in Customizable Environments to enable scalable compute with library management for reproducible research
Produce stunning visualizations directly from your data in real time, then quickly share using interactive Dashboards
Visually program for deep learning with an intuitive drag-and-drop, no-code interface in Neural Network Modeler
Uncover hidden insights from data with built-in data cleaning and transformations with Data Refinery
Use open-source tools like Jupyter Notebooks, combined with features like version control and programmatic access
Explore data and use machine learning with drag-and-drop tooling from SPSS Modeler - a new look on the classic tool
Improve your model's performance by visualizing fit between model and data, with Model Visualization within SPSS Modeler