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 Analytics Cloud. We take care of the infrastructure, setup and maintenance so you can focus on using the applications.
What is SAS® Analytics Cloud?
SAS Machine Learning is the first offering available on SAS Analytics Cloud – a powerful new way to get world-class software as a service (SaaS) from SAS. Running on the SAS Cloud and using the latest container technology, Analytics Cloud eliminates the need to install, update or maintain software or related infrastructure. Look for more offerings on Analytics Cloud in the future.
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 on Analytics Cloud 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 on Analytics Cloud 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 on SAS Analytics Cloud 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 on Analytics Cloud for free, 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, Analytics Cloud offers 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 on Analytics Cloud & Beyond
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Research
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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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Analyst Report
Hype Cycle for Data Science and Machine Learning, 2018Data and analytics leaders should use this Hype Cycle to understand technologies generating excitement and inflated expectations, as well as significant movements in adoption and maturity.
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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.
