Edit, review, and suggest changes to the content below as a comment to this issue. Use the image attached as a reference of what the content will be rendered like. If content and wording looks good. Give a lgmt (looks good to me) in the comments of this issue, otherwise leave your suggestions.
Current Content
Title: ML Engineer
Benefit 1
Title: Integration of open-source AI and ML tools:
Body: OpenDataHub.io is a community meta-operator that integrates best open-source AI, ML, and data projects. The platform provides open-source tools for distributed AI and ML workflows, Jupyter Notebook development environment, and monitoring. The integration of these tools makes it easy for ML engineers to build end-to-end AI/ML solutions on OpenShift, which is a container application platform.
Image: None
Other Features
Feature 1
Title: None
Body: None
Icon: None
Feature 2
Title: None
Body: None
Icon: None
Benefit 2
Title: Self-service provisioning of data processing:
Body: OpenDataHub.io offers self-service provisioning of data processing, analytics, and ML services to organizations. The platform provides machine learning services that allow ML engineers to process large and distributed AI workloads on the OpenShift Container Platform. The platform also offers a workshop that enables attendees to understand how to use OpenShift Container Platform, OpenShift Container Storage, and the Open Data Hub to provide self-service provisioning of data processing, analytics, and machine learning services to organizations.
Image: None
Other Features
Feature 1
Title: None
Body: None
Icon: None
Feature 2
Title: None
Body: None
Icon: None
Benefit 3
Title: Streamlined ML workflows:
Body: OpenDataHub.io offers a comprehensive platform that simplifies the process of creating, deploying, and managing machine learning (ML) models for ML Engineers. By integrating various tools, frameworks, and data sources in a single, unified environment, it reduces the complexity of ML workflows. Engineers can efficiently manage data, train and validate models, and deploy them in production without worrying about compatibility issues or managing multiple tools. This seamless integration saves time and effort, enabling ML Engineers to focus on model development and optimization.
Objective
Edit, review, and suggest changes to the content below as a comment to this issue. Use the image attached as a reference of what the content will be rendered like. If content and wording looks good. Give a
lgmt
(looks good to me) in the comments of this issue, otherwise leave your suggestions.Current Content
Title: ML Engineer
Benefit 1
Benefit 2
Benefit 3
Icon: None Design Example