SAS Visual Data Mining & Machine Learning Overview
An intuitive programming environment. Innovative algorithms. Fast, in-memory processing. SAS Visual Data Mining and Machine Learning shatters barriers related to data volume and variety, limited analytical depth and computational bottlenecks. That means greater productivity – and faster, deeper insight.
Machine Learning: What it is and why it matters
Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look.
The Evolution of Analytics: Opportunities and Challenges for Machine Learning in Business
Analytics is now an expected part of the bottom line. The irony is that as more companies become adept at analytics, it becomes less of a competitive advantage. Businesses are now being forced to look deeper into their data to increase efficiency and competitiveness.
Enter machine learning. Recent advances have led to increased interest in adopting this technology as part of a larger, more comprehensive analytics strategy. But incorporating modern machine learning techniques into production data infrastructures is not easy.
Read this report to learn more about modern applications for machine learning, including recommendation systems, streaming analytics, deep learning and cognitive computing. And learn from the experiences of two companies that have successfully navigated both organizational and technological challenges to adopt machine learning and embark on their own analytics evolution.
Statistics and Machine Learning at Scale
Machine learning uses algorithms to build analytical models, helping computers “learn” from data. It can now be applied to huge quantities of data to create exciting new applications such as driverless cars.
This Conclusions Paper, based on a presentation at the Analytics 2014 conference, introduces key machine learning concepts and describes new SAS solutions that allow data scientists to perform machine learning at scale. In the presentation, Viseca Card Services shares its experiences using machine learning to differentiate a new customer loyalty program
Machine Learning with SAS Enterprise Miner
This paper illustrates how a SAS team of modelers used SAS Enterprise Miner and 2009 KDD Cup competition data to create a highly accurate model for predicting churn. They applied several data preparation, feature creation and dimension reduction techniques to prepare the data for modeling. They then used several machine learning approaches, including an open source model that could be incorporated into SAS Enterprise Miner. The models were accessed using the assigned validation criteria. Learn how they approached the problem and which model was declared the “winner.”
An Overview of SAS Viya
SAS Viya is an open, cloud-ready, in-memory architecture that delivers everything you need for fast, accurate analytical results – all of the time. With its fluid, scalable and fault-tolerant processing environment, this resilient architecture addresses the complex analytical challenges of today with the ability to effortlessly scale into the future. SAS Viya provides:
- A modern, cloud-ready analytics architecture from the analytics market leader.
- A single, open and governed analytics environment with a standardized code base that can incorporate both SAS and other programming languages.
- A uniquely comprehensive and scalable platform for both public and private cloud implementations.