What types of APIs does this product expose?

The product exposes REST APIs for model management, training, and deployment. Specific endpoints include `/model`, `/training`, and `/deployment`. It supports integration with Python and Java SDKs.

What protocols does it use for communication?

Communication occurs over HTTPS. The system supports standard protocols for data transfer and model deployment.

What are the main system components?

The main system components include the Model Management Service, Training Service, and Deployment Service. These components communicate via REST APIs and message queues.

How does IBM Machine Learning for z/OS provide business value?

IBM Machine Learning for z/OS automates the creation, training, and deployment of operational analytic models. This reduces the time and resources required for machine learning projects.

What are the benefits of using this product with z/OS data?

The product allows machine learning against z/OS-based data, enabling organizations to leverage their existing data assets for AI initiatives.

What authentication methods are supported?

The product supports authentication methods including LDAP, SAML 2.0, and X.509 certificates. It uses Role-Based Access Control (RBAC) to manage user permissions.

What encryption is used and where?

Data is encrypted in transit using TLS/SSL. Data at rest can be encrypted using z/OS encryption facilities.

What audit/logging capabilities exist?

The system provides audit logging capabilities, recording user actions and system events. These logs can be used for security monitoring and compliance.

What administrative interfaces are available?

Administrative interfaces include a command-line interface (CLI) and a web console. User management is handled through the web console or via LDAP integration.

What are the main configuration parameters?

The main configuration parameters are defined in YAML files. These parameters control model training, deployment settings, and system behavior.

What monitoring/logging capabilities exist?

The system provides monitoring and logging capabilities through the web console and system logs. Metrics can be exported to external monitoring tools via APIs.

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IBM Machine Learning for z/OS

Name: IBM Machine Learning for z/OS
Availability: InStock

IBM Active z/OS

Application - Other Data Discovery Mining and Processi

Vendor

IBM

Product Overview

The architecture of IBM Machine Learning for z/OS comprises several key components. The Model Management Service provides a central repository for machine learning models. The Training Service handles the execution of model training jobs, leveraging frameworks like Apache SparkML and TensorFlow.

The Deployment Service manages the deployment of models for scoring. These components communicate via REST APIs and message queues. Data is stored in z/OS datasets and can be accessed directly by the training and deployment services.

Configuration is managed through YAML files, which define parameters for model training and deployment. 509 certificates, with RBAC for access control. Network requirements include open ports for REST API communication and data transfer.

ai offer similar functionality, but IBM's solution is unique in its deep integration with the z/OS platform, allowing direct access to mainframe data without the need for data replication.

Frequently Asked Questions

What are the common operations performed with IBM Machine Learning for z/OS?

IBM Machine Learning for z/OS allows users to build, train, and deploy machine learning models. Common operations include data preparation, model selection, training, evaluation, and deployment. Users interact with the system through REST APIs, command-line interfaces, and configuration files.

What configuration files or interfaces are used?

Configuration files, such as YAML files, are used to define parameters for model training and deployment. The system also provides a web-based user interface for managing models and deployments.

What programming languages and machine learning frameworks are supported?

IBM Machine Learning for z/OS supports languages including Scala, Java, and Python. It also supports machine learning frameworks including Apache SparkML, TensorFlow, and H2O.

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