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.
Faster coding of machine learning algorithms
Reduces the learning curve and expedites model development with automatic code generation and reusable code snippets.
Hyperparameter autotuning
Enables faster, better model results with best-in-class hyperparameter autotuning.
More efficient programming
Boosts programming efficiency with autocomplete capabilities, syntax help, color coding, keyword shortcuts and more.
Advanced data transformation
Provides robust coding language for data transformation and manipulation.
Collaboration across languages
Lets you code in your preferred programming language – SAS or Python.
Analytics life cycle navigation
Provides a single interface that facilitates fast, efficient movement from data preparation, to exploration, to model development.
Easy, cloud-based access to data science applications
Provides instant access to powerful data science applications via SAS Cloud. We take care of the infrastructure, setup and maintenance so you can focus on using the applications.
Sign up, sign in and get to work.
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.
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White Paper
How to Do Deep Learning With SAS® Get an introduction to deep learning techniques and applications, and learn how SAS supports the creation of deep neural network models.
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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.
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Article
Machine learning and artificial intelligence in a brave new worldWhat is the interplay between man and machine in a brave new world with AI?
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White Paper
Advanced Analytics: Moving Toward AI, Machine Learning, and Natural Language ProcessingThe global excitement around the latest advancements in artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) technologies has increased with the evolution of computing power.
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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.
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White Paper
BI, Analytics, and the Cloud: Strategies for Business AgilityThis TDWI Research report examines organizations’ experiences with, and plans for, cloud BI and analytics, new cloud models, and what should be considered when moving to the cloud.
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White Paper
Demystifying AnalyticsTo educate and inform insurance companies about how they can move toward becoming an “analytic insurer” – one that embeds analytics into daily operations to make better decisions that reduce costs, improve pricing and more.
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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.
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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.
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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.
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White Paper
Machine learning and artificial intelligence in a brave new worldMachine learning in the last few decades has given way to an AI revolution. From self-driving cars to virtual assistants, learn more about the endless possibilities for these developing technologies.
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White Paper
Hosted Managed Services for SAS® TechnologySAS provides hosted managed services designed to provide faster and easier deployment options for SAS technologies. This white paper reviews the fundamentals of this capability.
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Article
4 strategies that will change your approach to fraud detectionTechnology advances are giving financial institutions a better arsenal than ever for fraud detection. Take a look at four ways to turbocharge your defenses.
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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.
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White Paper
Machine Learning Use Cases in Financial CrimesLearn 10 proven ways machine learning can boost the efficiency and effectiveness of fraud and financial crimes teams – from data collection to detection to investigation and reporting.
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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?
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White Paper
Machine Learning With SAS® Enterprise Miner™Learn how SAS modelers prepared data and applied different machine learning techniques to create and identify the most accurate model for predicting churn using KDD Cup data.
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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.
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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.
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Article
How to drill a better hole with analyticsFrom drilling holes to preventing health care fraud, learn about some of the new technologies SAS has patented with IoT and machine learning technologies.
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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.
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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.
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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.
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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.
