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autoai

covid-19-sas

Collaboration space for SAS and others to understand, model, and mitigate COVID-19 through analytics

demos

devsascom-rest-api-samples

This repository contains examples that show the capabilities of SAS REST APIs. You can use these examples for learning or for validating your environment. You are encouraged to contribute your own examples.

enlighten-apply

Example code and materials that illustrate applications of SAS machine learning techniques.

gentle-intro-stats-using-sas-studio

This repository contains the sample code for the book A Gentle Introduction to Statistics Using SASⓇ Studio.

ibm-generative-ai

IBM-Generative-AI is a Python library built on IBM's large language model REST interface to seamlessly integrate and extend this service in Python programs.

machine-learning

Content for Udacity's Machine Learning curriculum

model-mgmt-on-watson-studio-local

Feature Engineering and Model Deployments using Watson Studio Local

open-model-manager-resources

This repository contains the start-up script for SAS Open Model Manager, as well as helper scripts for administration and customization.

python-dlpy

The SAS Deep Learning Python (DLPy) package provides the high-level Python APIs to deep learning methods in SAS Visual Data Mining and Machine Learning. It allows users to build deep learning models using friendly Keras-like APIs.

python-sasctl

The sasctl package enables easy communication between the SAS Viya platform and a Python runtime.

sas-visualanalytics-thirdpartyvisualizations

The data-driven content object enables you to display your data in a custom third-party visualization, within your SAS Visual Analytics report. The third-party visualization can be authored in any JavaScript charting framework, such as D3.js, Google Charts, or CanvasJS. The visualization in a data-driven content object receives its data query from SAS Visual Analytics, and so it interacts with filters, ranks, and object actions in the same way as the other objects in your report. For information about creating third-party visualizations for data-driven content, see Programming Considerations for Data-Driven Visualizations in SAS Visual Analytics: Reference.

sas-viya-dmml-pipelines

Code examples and supporting materials for data mining and machine learning techniques on the SAS Viya environment.

sas-viya-machine-learning

Code examples for machine learning techniques using the SAS Viya platform.

saspy-examples

Sample notebooks that show the capabilities of SASPy. Use these for learning and for validating your environment. And contribute your own!

tensorflow

Computation using data flow graphs for scalable machine learning