Many problems in analytics and data science are often solved using a binary classification model. A binary classification model has two possible outcomes, such as Yes or No and True or False. But not all problems fit neatly into two categories.   In fact, the popular (and not so cool anymore let's face it) Iris Data Set features three possible outcomes: one for each Iris species in the sample. And of course, there are prediction models as well, whose predictions fall along a continuum.     SAS Model Manager fully supports binary classification and prediction models already. But with the release of SAS Model Manager 2021.2.6, we’ve baked-in broader support for multinomial classification models. This includes metadata support for target event values and performance monitoring for multinomial classification models. The Project Properties pane in SAS Model Manager lists the possible event values for multinomial models and can automatically discover those values.       Additionally, Performance Monitoring includes charts and metrics that are specific to Multinomial models.         Learn more about our new features for multinomial models in the following video:    We are continuing to expand our support for various types of models. What kinds of model support would you like to see within Model Manager? Leave your comment below!   ... View more

One of our goals at SAS is to allow users to interact with SAS Viya in the way that makes the most sense to them. For data scientists using Python, that is often through our open-source packages, such as SWAT and sasctl. Thus, it is important that we continue development in our open source packages. In this blog, we will briefly discuss sasctl as well as introduce its integration with git.    First things first. What is sasctl?  Sasctl is an open-source package developed by SAS that allows Python data scientists to easily communicate with the model management capabilities of the SAS Viya platform. It gives you the ability to register models and modeling assets into SAS Model Manager directly from a Python IDE! Python Zip Model Management functionality, also known as PZMM, exists within the sasctl package.  Sasctl supports a wide variety of Python model packages including fan-favorites sklearn and xgboost.      Introducing Integration for Git  Git is a free and open-source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. Many organizations use git for tracking changes in files and collaborating on code. While data scientists may be leveraging git to develop models over time, it lacks the context that is necessary to truly manage models. SAS Model Manager adds a layer of governance, management, care, and control to these models. So, we are excited to further our integration with git to better support analytically needs across organizations!    To get started using our sasctl integrations git, check out this notebook or follow along with the steps below.     Get Started  To start leveraging sasctl with git, complete the following steps:  Download and install git.   Create a local repository in git that is accessible to your Python environment. (Note: to learn more about git, check out this book).   Optional: Add remote origin to the local git repository.   Install sasctl in your Python environment.   Import sasctl in your Python code.   Specify the path of your local repository.  Start SAS Viya session through sasctl.   Now we are ready to start using sasctl with git. Our integrations include:  Pulling a model from SAS Model Manager into a local git repository.   Pulling a project from SAS Model Manager into a local git repository.   Pushing a model from a local git repository into SAS Model Manager.   Pulling changes from a remote git repository into a local git repository.   Pushing changes from a local git repository into a remote git repository.  The following video walks through each of the steps with code:      Other Resources  Want to learn more about SAS Model Manager, sasctl, and git? Check out the following links!  Using SASCTL package to deploy and manage MLflow models - a step by step introduction  Register a Python model using the Python Zip Model Management (pzmm) module  What's New with SAS Model Manager? pzmm (Python Zip Model Management) module updates  Git as a SAS Model Manager Publishing Destination  SASCTL Examples  ... View more

Model Manager is the MLOps solution as part of Viya, the AI and Analytics enterprise platform launched in 2017 by SAS.    The objective of an MLOps team is to automate the deployment of ML models into the core software system or as a service component. This means, to automate the complete ML-workflow steps without any manual intervention. Triggers for automated model training and deployment can be calendar events, messaging, monitoring events, as well as changes on data, model training code, and application code.    The SAS MLOps team has worked hard in the past months to offer an improved user experience when building MLOps workflows, adding the latest Workflow Manager as part of Model Manager, the MlOps tool. Check out this article to know what is Workflow Manager and how it works.   In today's blog, I want to share some of the newest additions over the past months.    In 2021.2.4, we’ve added autosave capabilities, so that your workflow automatically saves upon closing. Also in 2021.2.4, we’ve added the ability to configure custom notification templates. Notification templates define email and message templates that are sent to users when a Send Notification or Send Group Notification task is added to the workflow. This allows workflow designers to populate the notification with actional information that can be used directly for decision making. Workflow designers can embed data objects within the notification, preview the notification, and send a test notification, so that they can be certain that information is flowing into the notification correctly.     In 2021.2.3, we’ve added the ability to include custom attributes within prompts. This allows solutions that use SAS Workflow Manager to pull specific data from the solution into the prompts. For example, SAS Model Manager has two available attributes:  show_model_list, which shows a list of models in the current project and select_potential_owner, which launches the Choose Members window. Learn more about these attributes and how to leverage them in the demo video below!       We’ve also enhanced the Instance category view so that Workflow Admins can see when the tasks started and how long they took to complete. This provides insight into bottlenecks within the flow.         And finally, we have been improving how errors are viewed within the Instance category view. Whenever a Service Task fails, the failure is noted on the diagram and table. Clicking the failure icon in the table opens an error pane with the returned error. This helps Workflow Designers better pinpoint why errors are occurring to quickly address and fix them.       What else would you like to see in Workflow Manager? Let me know below!   What to learn more about  Workflow Manager? Check out the following links! SAS® Workflow Manager: Quick Start Tutorial Building Performance Monitoring Processes in SAS Workflow Manager Automating Model Life Cycle Management with SAS Model Manager and SAS Workflow Manager Free ebook on "Mastering Model Lifecycle Orchestration"  ... View more

With the release of SAS Model Manager on 2021.1.6, we have implemented a new easy way to share what you are working on with your teammates.   A new sharing icon has appeared in the upper right corner of the interface, which allows users to easily share models, projects, and specific views via a link or directly to Microsoft Teams! This helps teams collaborate faster.  Need someone to look at something? Send them a message within Microsoft Teams with just a few clicks. Not using Microsoft Teams? Simply copy and paste the link into your messaging service of choice!    Get started   Check out this short video for a step by step overview of the new capability!     What to learn more about what’s new in Model Manager? Check out the following links!  What’s New with SAS Model Manager? SAS Container Runtime Publishing to Google Cloud Platform  What's New with SAS Model Manager? Deployments view  What's New with SAS Model Manager? Integration with SAS Model Risk Management  ... View more

It’s no secret that SAS Viya is a platform that supports the entire analytics lifecycle and allows a wide variety of users with different skills to collaborate.  To better support our users, we want to ensure that they can interact with SAS Viya in the way that makes the most sense to them. For data scientists using Python, that is often through our open source packages, such as SWAT and SASCTL. In this blog, we will explore what is SASCTL and introduce the new integration with MLflow.   What is SASCTL? 🧐 SASCTL is an open source package developed by SAS that allows Python data scientists to easily communicate with the SAS Viya platform. It can be used as a module or as a command line interface and gives you the ability to register models and modeling assets into SAS Model Manager directly from a Python IDE! Python Zip Model Management functionality, also known as PZMM, exists within the SASCTL package.  SASCTL supports a wide variety of Python model packages including fan-favorites sklearn and xgboost.     Introducing support for MLflow 🔗 Many data scientists are leveraging MLflow, an open source MLOps platform, for managing modeling assets. To better support these users, we are integrating SASCTL with MLflow. We currently support using SASCTL to generate and register modeling assets for MLflow models developed using a variety of common Python packages (such sklearn, statsmodels, scipy, and numpy) with plans to expand to more complex modeling packages.    Get started ⬇️ To start leveraging SASCTL with MLflow, complete the following steps:   Install sasctl and MLflow to your Python environment.   Import sasctl, MLflow, and infer_signature from mlflow.models.signature in your Python code.   Build your model.   Create the MLflow signature.   Add the signature as a parameter for the MLflow logging function.  Point the pzmm.MLFlowModel.readMLmodelFile() function of sasctl to the MLflow files.  Generate the model metadata using sasctl.  Register model into Model Manager using pzmm.ImportModel() function of sasctl. Use Model Manager to test, deploy and monitor the model. 🎥 The following video walks through each of the steps with code:      Other Resources  Want to learn more about SAS Model Manager and Python Models? Check out the following links!   SASCTL Complete Model Example Notebook  SASCTL Model Import Example Notebook  SASCTL Examples  Register a Python model using the Python Zip Model Management (pzmm) module  What's New with SAS Model Manager? pzmm (Python Zip Model Management) module updates  SAS Developers resources If you liked the article, leave a comment below on what other enhancements you want to see to SASCTL! ... View more

Welcome back and Happy 2022 Model Manager's users! 👨‍💻👩‍💻👩🏾‍💻👨🏾‍💻🎉   With the January release on SAS Viya 2021.2.3, ModelOps engineers can deploy, execute, and validate SAS Container Runtime (SCR) containers in the Google Cloud Platform (GCP). This extends our support across the leading cloud providers to provide coverage for our Viya 4 customers in GCP, Azure, Amazon Web Services (AWS) and private Docker registries.   As a reminder, SCR became available in the SAS Model Manager 2021.1.3 and allowed users to publish SAS models using a lightweight container. SCR provides a modern, bullet proof, reliable, non-proprietary system for transferring and executing runtime code. ModelOps engineers can leverage cloud infrastructure or local installation to deploy highly scalable and highly available applications with small footprint.   Get started by watching this short video tutorial!       We will continue working on improving SCR publishing so that ModelOps engineers can create a seamless model deployment process within their production environments of choice. Stay tuned!    🚀 Do you have any recommendation on the roadmap? Let us know in the comments what feature would you like to see in the future.   👉 We also love sharing how people are using SAS Model Manager. Share your work on your favorite social channel, using the hashtag #iusesasmodelmanager and tagging SAS, and we will reshare you story.   For more information about using SAS Model Manager with SAS Container Runtime, refer to the SAS Model Manager: User’s Guide documentation.   Want to learn more about SCR and other publishing destinations? Check out the following Links! What's New with SAS Model Manager? SAS Runtime Container How to Publish a SAS Model to Azure with SCR: A Start-to-Finish Guide Using the SAS Container Runtime for publishing SAS models to Kubernetes on the Azure cloud ModelOps and DecisionOps for the Modern World SAS® Container Runtime: Programming and Administration Guide SAS Container Runtime GitHub ... View more

Open source technology, packages, and languages are being adopted by businesses to analyze data, develop models, etc. But, there are still lots of questions. How is SAS helping?   In companies who started an AI pilot before 2019, 72% of them has not deployed any single application. Models aren't being deployed and if they are, they break because of changes in data, external conditions, business objectives etc.   Watch this Ask the Expert session to learn how SAS Viya integrates with open source technologies by improving interoperability and utility for the enterprise, provides governance, monitoring, interpretability, responsible AI, and choice of language to simplify collaboration between data scientists, IT, and business users.   Watch the webinar   You will learn 💎: Which open source languages are mainly being adopted and why. What challenges are companies facing with AI & Analytics. How SAS Viya integrates with open source to overcome challenges. The benefits of using SAS Viya with open source technology.       The questions from the Q&A session held at the end of the webinar are listed below and the slides from the webinar are attached.   Q&A How does SAS integrate with Tableau? We have different integration scenarios and the best one is defined on the basis of customers needs.  Different options include: SAS has APIs and SDKs (developer.sas.com) that can allow an organization to customize and build applications that can bring insights from SAS and Tableau together. SAS Visual Analytics allows 3 rd party graphic integration (such as D3 charts, HTML content) .Graphics published from Tableau in those formats or data from Tableau supporting a D3 graphic result could potentially be accessed inside a SAS report. SAS interactive visual insights can be published as data stories (interactive HTML pages) that can be embedded in Tableau – if their application supports embedding HTML content from external sources. When connecting to CAS with SWAT in Jupyter Notebook, does this enable me to utilize the computing power of Viya when running my Python code? If so, what runs locally and what runs on the server? How do I specify what I want to run locally and what I want to run on Viya? Only the actions you submit through SWAT run in CAS.  All other native python code runs in your local python instance.  This is idea. – you can do big data work in CAS and all other work can run locally.     Does SAS internally convert Python code to SAS code when dealing with SAS datasets? No.  However, SWAT will convert data sets  but not python code.  In a separate case, The SAS DS2 PYMAS package will allow you run correctly-coded Python functions within the CAS DS2 action, which can cover simple transformations to full gradboost or pytorch models.     Is there a visual demo that you know of or a use case on the SAS website that shows how Python is integrated with SAS code? Does SAS internally convert Python code to SAS code when dealing with SAS datasets? There are actually several visual demos on our SAS Users YouTube channel. We have just posted videos about this. SAS does NOT convert python code to sas code. However, SWAT will convert data sets  but not python code. In a separate case, The SAS DS2 PYMAS package will allow you run correctly-coded Python functions within the CAS DS2 action, which can cover simple transformations to full gradboost or pytorch models.     Is the Integrated ModelOps framework a standard part of SAS Viya? Yes, it is part of SAS Viya and it is called SAS Model Manager.   How does SAS support open source in the model deployment and management phase?  SAS support SAS and open source models (python,R,java etc), enabling users to collect, compare, test, version, monitor, govern, deploy, retrain etc every type of model and score code in the cloud, on premise, real-time...   SAS Does not translate Python code into SAS code statement, right? Correct.  However, the SASPY project provides a custom Python package that will generate new SAS code statements.    Recommended Resources Drive Analytic Innovation with SAS and open source integration Mastering Model Lifecycle orchestration – An interactive guide SAS and open-source model management (free ebook) SAS Visual Data Science Decisioning Trial (free for 14 days) Empowering open integration with SAS Viya video series SAS Learning Conference   Want more tips? Be sure to subscribe to the Ask the Expert board to receive follow up Q&A, slides and recordings from other SAS Ask the Expert webinars.     ... View more

Hi Developers Community 😄,    I’m presenting a live “Ask the Expert” webinar on October 21 th , 11 – 11:45 AM ET entitled But I Love Open Source – Why Do I Need SAS ® Viya ® ? I’ll show you how SAS Viya works with open source technologies, tools and libraries by improving interoperability and utility for the enterprise, streamlining the work between data scientists and IT and reducing time to value.      ‼️ Bring your questions. I’ll also host a live Q&A session at the end of the webinar.   💎 You will learn: About the open source ecosystem. How SAS Viya works with open source. The benefits of using SAS Viya with open source technology.  👉🏻 Reserve your spot for the webinar.   Want more tips?💡Be sure to subscribe to the Ask the Expert board to receive follow up Q&A, slides and recordings from this and other SAS Ask the Expert webinars.   Can't join the live event? Help us spread the word but sharing this post with your network. Thank you! 🙏   You can view this and other Ask the Expert sessions on-demand here.    ... View more

Hi SAS Viya Community 😄,    I’m presenting a live “Ask the Expert” webinar on October 21 th , 11 – 11:45 AM ET entitled But I Love Open Source – Why Do I Need SAS ® Viya ® ? I’ll show you how SAS Viya works with open source technologies, tools and libraries by improving interoperability and utility for the enterprise, streamlining the work between data scientists and IT and reducing time to value.      ‼️ Bring your questions. I’ll also host a live Q&A session at the end of the webinar.   💎 You will learn: About the open source ecosystem. How SAS Viya works with open source. The benefits of using SAS Viya with open source technology.  👉🏻 Reserve your spot for the webinar.   Want more tips?💡Be sure to subscribe to the Ask the Expert board to receive follow up Q&A, slides and recordings from this and other SAS Ask the Expert webinars.   Can't join the live event? Help us spread the word but sharing this post with your network. Thank you! 🙏   You can view this and other Ask the Expert sessions on-demand here.  ... View more