IBM Cloud Pak for Data is a unified , pre-integrated Data and AI platform based on Red Hat OpenShift Container Platform with services delivered with an open and extensible cloud native platform for collecting, organizing, analyzing and infusing your data. Get started with these developer resources, so you can quickly accelerate your journey to AI by building systems of insight through governed data and governed AI.
Visit our Developer Hub
to kick off your journey on our Data and AI Platform. Click here to Test drive IBM Cloud Pak for Data for free with a 7-day trial. No installation required.
Try out the basic Getting Started Learning Path to virtualize your data, visualize and transform your data, and lastly, build and deploy your model using Jupyter Notebooks.
Code Patterns and Templates
SDKs Introduction to IBM Cloud Pak for Data
Learn about the collect, organize, analyze, and infuse AI using IBM Cloud Pak for Data in this article.Learn more about the services in Cloud Pak for Data. For more details please visit our Product Documentation.
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This section contains the API reference documentation for Cloud Pak for Data.
IBM Cloud Pak for Data API’s are an integral part of the pre-integrated platform with services delivered in an open and extensible cloud native platform for collecting, organizing, analyzing data and ultimately infusing AI into your applications. The open and extensible collection of REST API’s give you the power to automate, govern and operationalize AI lifecycle in business applications and implement data-driven processes and operations to support development of AI and ML capabilities.
On Cloud Pak for Data platform, note that you can access all of the following categories of APIs from your applications using the single token based authentication and authorization APIs in the administration section included below.
||The platform set of APIs facilitates programmatic management of users and their access control, along with, user account management – authentication, password management, and user profile editing.
|Collect and Organize APIs
||This collection of API’s includes capabilities to manage connections in analytics projects and catalogs. It also includes search, data governance, discovery, data quality and active policy management with data lineage to help understand and govern assets.
||The Analyze APIs provides you with services to build, train, and deploy analytical models and neural networks that you can deploy and use in your applications through a continuous machine learning deployment cycle.
||These API’s help to track and measure the outcomes of your AI models ensuring they remain fair, explainable, and compliant; thus helping you correct the drift in accuracy for your models in production.
|Watson Application APIs
Watson Discovery APIs
These APIs provide capabilities for cognitive search and content analytics engine that you can add to applications to identify patterns, trends and actionable insights to drive better decision-making.
Watson Assistant APIs
These APIs combine machine learning, natural language understanding to create conversation flows between your apps and users.
Watson API Toolkit APIs
This toolkit provides the capability to combine and choose several Watson APIs within one offering with the goal of building AI applications or enhancing other applications.
Natural Language Understanding
Speech to Text
Text to Speech
Code Patterns and Templates
Code patterns and templates offer up complete solutions to problems that developers face every day.
Code patterns leverage multiple technologies, products, or services to solve issues that our developer advocates have recognized as common use cases across multiple industries.
Install and configure Cloud Pak for Data on Red Hat OpenShift Container Platform using Red Hat OpenShift templates on IBM Cloud or through a custom user-registry on-prem.
Explore the following Code Patterns
that will help you use Cloud Pak for Data along your AI journey to govern and understand the quality of your data, build and manage your models in production, and measure your model accuracy and mitigate bias with one-click Git repos, documentation, and resources.