Combining data preparation, feature engineering, modern statistical and machine learning techniques in a single, scalable, in-memory processing environment for developing, testing and deploying models.
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Quickly identify patterns, trends and relationships in structured and unstructured data.
With no software to install and simplified, user-based licensing, SAS Machine Learning gives you fast, easy access to a broad set of modern statistical, machine learning, deep learning and text analytics algorithms. This includes neural networks, clustering, different flavors of regression, forest, gradient boosting models, support vector machines, natural language processing, topic detection and others. Having access to these leading-edge algorithms drives innovation and enables you to uncover new patterns, trends and relationships between data attributes in structured and unstructured data.
Spend less time number crunching, more time generating meaningful insights.
Use autotuning capabilities to automatically find the best set of machine learning hyperparameters or properties based on your modeling objective. And take advantage of built-in optimization solvers to build optimal models in the shortest amount of time. The automated capabilities of SAS Machine Learning empower you to spend more time gleaning meaningful insights from your data by letting SAS crunch the numbers for you.
Take advantage of a powerful, collaborative coding environment for both SAS® and Python programmers.
In addition to using the SAS language, you can access SAS algorithms from Jupyter Notebook using Python. SAS Machine Learning provides a unified experience for generating models, assessing output and gaining insights. You can access the same machine learning algorithms and data that are available via SAS programming in SAS® Studio.
Try it. Love it? Buy it.
Try SAS Machine Learning and see firsthand how easy it is to get programmatic access to some of the most powerful data science applications available – featuring world-class SAS Analytics. If you like SAS Machine Learning, we offer simplified licensing with a try-to-buy path that features user-based pricing, self-administration, and the ability to share projects and data with other team members.
Explore More on SAS® Machine Learning & Beyond
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- White Paper Data Mining From A to ZThis paper shows how you can use predictive analytics and data mining to reveal new insights from data, as well as get all the pieces and parts moving together for maximum value.
- Article Exploring the sun with big dataResearchers working for NASA are using automatic, exploratory and visual analysis of big data to help understand the mysteries of our universe.
- Analyst Report Bloor InBrief: SAS Event Stream ProcessingLearn why Bloor considers SAS a major contender in the market for streaming analytics platforms due to SAS’ differentiating analytic capabilities, notable performance and continuous improvement of in-stream models using machine learning.
- White Paper Heavy Reading: Advanced Predictive Network AnalyticsHeavy Reading reveals how predictive analytics gives service providers real-time visibility into their networks – boosting revenue potential and ensuring more satisfied customers, better targeted marketing, fine-tuned capacity planning and top-notch service assurance.
- Article Stopping the Zika virus: The potential of big data, analyticsHow do you stop global outbreaks? The answer may be in the data about the disease and how it spreads.
- White Paper Analytics Across the Student Life CycleWhy higher education institutions need to implement data integration, data visualization and analytics solutions. It then shares best practices for applying these technologies across the student life cycle and examples of how schools are using these technologies to improve decision making.
- White Paper Advanced Analytics: Moving Toward AI, Machine Learning, and Natural Language Processingadvanced analytics, artificial intelligence, machine learning, natural language processing
- White Paper BI, Analytics, and the Cloud: Strategies for Business AgilityCloud BI and analytics
- Article Detect and prevent banking application fraudSince credit fraud often starts with a falsified application, it makes sense to have analytics-driven tools in place to detect fraud from the earliest point and across the life of the account.
- Article Analytics: A must-have tool for leading the fight on prescription and illicit drug addictionStates and MFCUs now have the analytics tools they need to change the trajectory of the opioid crisis by analyzing data and predicting trouble spots – whether in patients, prescribers, distributors or manufacturers. The OIG Toolkit with free SAS® programming code makes that possible.
- White Paper Enabling Data and Analytics in the CloudRunning analytics software in the cloud can vastly simplify the deployment, maintenance and adoption of analytics across the enterprise. But it does add another level of complexity to operations – complexity that must be managed by experts.
- White Paper Bring Your Analytics Investments into the Cloud-Native World: Key Best PracticesChecklist report on migrating enterprise data analytics investments to the emerging cloud-native world of distributed containerized applications.
- Analyst Report Gartner positions SAS as a Leader in the Magic Quadrant for Data Science and Machine Learning Platforms, Q1 2021Gartner positions SAS as a Leader in the Magic Quadrant for Data Science and Machine Learning Platforms for the eighth consecutive year.
- Article A guide to machine learning algorithms and their applicationsDo you know the difference between supervised and unsupervised learning? How about the difference between decision trees and forests? Or when to use a support vector algorithm? Get all the answers here.
- E-Book Discovering new possibilities with SAS® Viya® on Microsoft AzureOrganizations need to quickly solve complex problems and make decisions. That’s exactly what SAS Viya on Microsoft Azure was designed to do. You get powerful, easy to use analytics that incorporate open source and SAS algorithms on a scalable, easy to deploy environment.
- White Paper Delivering SAS® Expertise to Your DoorSAS Remote Managed Services fulfills customers’ application management needs when they require or prefer that the solution and data remain on-site. Learn how this offering can help your organization deliver insights from your analytics program.
- E-Book Delivering Insight and Innovation With SAS® Viya® on Microsoft AzureData analytics can only drive success if it enables intelligent decision making. A cloud-based analytics platform can provide the agility to experiment quickly to generate fast insights from data. This e-book shows how organizations can use advanced analytics in the cloud.
- Article Five AI TechnologiesDo you know the difference between artificial intelligence and machine learning? And can you explain why computer vision is an AI technology? Find out in this short explainer.
- Article Discover a secret resource for working with cloud providersAre you overwhelmed by the hundreds of options and offers in the cloud? Are you finding it hard to select the best cloud services from the different cloud providers? Why not ask a neutral and informed third party for help?
- White Paper Field Experience in Embedded AnalyticsFast-track selected analytics into the could by leveraging expertise, using the latest methods, and focusing on the end state. Find ways to create more business value with analytics in the cloud – and ways to get there faster.
- Article 5 ways to measure beehive health with analytics and hive-streaming dataThis analytical approach to understanding bee hive health can automatically alert beekeepers to changes in hive weights, temperatures, flight activity and more.
- White Paper Artificial Intelligence for ExecutivesThis paper outlines the SAS approach to AI and explains key concepts. It also provides process and implementation tips if you are considering adding AI technologies to your business and analytical strategies.
- Article Fraud detection and machine learning: What you need to knowMachine learning and fraud analytics are critical components of a fraud detection toolkit. Here’s what you’ll need to get started – from integrating supervised and unsupervised machine learning in operations to maintaining customer service while defending against fraud.