How Data Science and MLOps is used
Data access, prep and pipelines
Right data, at the right time for the right user
Use fairness scores to improve bias reduction. Provide complete views of quality, secured data for permission-based, self-service access.
Building and deploying
Accelerate and scale production
Build and deliver models using MLOps to decrease costly human errors, improve workload efficiency and speed time to analytic insights.
Monitoring and retraining
Proactively detect and correct
Automate the detection of model degradatiom, drift and bias for model retraining and the need to retire
Benefits of Data Science and MLOps
Make trusted data available
Empower data scientists with self-service access to the right data for their project.
Speed time to AI insights
Build and move models into production quicker using automated tools and delivery.
Eliminate manual processes
Automate error prone, time intensive tasks so data scientists can focus on value-add initiatives.
Automate collaboration between the growing number of stakeholders with automated workflows
Monitor, track and retrain AI models
Ensure models work effectively and meet today’s ethical risk and regulatory concerns.
IBM Watson Studio recognized as Leader in IDC's Worldwide Machine Learning Operations Platforms 2022 Vendor Assessment
Capabilities of IBM Data Science and MLOps Solutions
Integrated visual tooling
Prepare data quickly and develop models visually with IBM SPSS Modeler in IBM Watson® Studio.
Model training and development
Build experiments quickly and enhance training by optimizing pipelines and identifying the right combination of data.
Extensive open source frameworks
Bring your model of choice to production, track and retrain models using production feedback.
Embedded decision optimization
Combine predictive and prescriptive models to optimize decisions. Create and edit models in Python, in OPL or with natural language.
Model management and monitoring
Monitor quality, fairness and drift metrics. Select and configure deployment for model insights. Customize model monitors and metrics.
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Data Science and MLOps case studies
Learn how IBM customers are using Data Science and MLOps to create innovative solutions.
IBM Watson® Studio
Simplify model production from any tool, automate model retraining and monitor for accuracy.
IBM Watson® Knowledge Catalog
Automate metadata collection and policy management.
News and events
Deep learning workloads
Optimize deep learning with IBM Cloud Pak for data
See which topics are most pressing and how a data fabric can help
Learn how to break down barriers to enterprise AI on IBM Cloud Pak for Data
Data Science and MLOps: An overview
Learn about common Data Science and MLOps challenges and how IBM solves them though IBM Watson Studio