Pre-processing and exploring data, building and deploying models and turning those scoring values into an actionable insight can be overwhelming. A recent survey... Pre-processing and exploring data, building and deploying models and turning those scoring values into an actionable insight can be overwhelming. A recent survey shows that for data scientists, the many tasks they spend their time working on are very different from the tasks they actually want to prioritize. This disparity can feel wide, especially when coworkers or internal clients think you can do it all. The expectations for those who work with data and analytics can be as large as the potential impact that can be made in organizations.

This course covers the theoretical foundation for different techniques associated with supervised machine learning models. In addition, a business case study is defined to guide participants through all steps of the analytical life cycle, from problem understanding to model deployment, through data preparation, feature selection, model training and validation, and model assessment. A series of demonstrations and exercises is used to reinforce the concepts and the analytical approach to solving business problems. This course uses Model Studio, the pipeline flow interface in SAS Viya that enables you to prepare, develop, compare, and deploy advanced analytics models. You learn to train supervised machine learning models to make better decisions on big data.

Artificial Intelligence (AI) is built on data. Yet, many organizations are still finding it hard to implement AI properly to make the most out of their data. There are concerns that the AI is not able to comprehend the data the way they want it to, especially with more businesses having their data stored across the multi-cloud and even on-premise. When it comes to data analytics, SAS has been a household vendor in the industry for years. The data analytics leader continues to pioneer new innovations when it comes to providing businesses with the insights they need in the best way possible.

The University of Alberta uses SAS Viya to help its researchers expand their capacity for big data analysis and support the use of open source software and other tools popular among students. Conducting research is not a straightforward process, and the terabytes of data cascading into labs (both physical and virtual) requires serious horsepower to analyze. Personal desktops and small servers are increasingly coming up short in meeting the demands of artificial intelligence and machine learning projects. Data also comes in various shapes and sizes. Researchers often combine data related to diagnostic imaging, risk prediction, clinical trials and much more.

I read analyst reports to keep myself up to date with what is going on in the analytics and AI world. An analyst report offers an unbiased, side-by-side, third-party evaluation of the technology in the market. I trust them because I have lived through the rigorous evaluation process that goes on behind the scenes for creating those reports. The recently released 2021 Gartner MQ for Data Science and Machine Learning contains a wealth of information and here are my takes on key market trends from that report for data scientists. This evaluation features SAS Viya with its SAS Data Science offerings.

Safety, efficacy, speed and costs must all be prioritized and balanced in the delivery of life-changing therapies to patients. A drug that's quickly and cost-efficiently delivered to market, but isn't effective and safe is unacceptable. An effective, safe drug that doesn't get to patients in time to save lives has failed those who needed it most. When it comes to patient health and safety, there can be no compromises. Fortunately, in a world with abundant data and advanced analytics, we have more tools than ever before to optimize this balance for the betterment of patient safety and outcomes.

Analytics leader SAS continues to innovate by making it easier to access its powerful, cloud-native SAS Viya platform. Recent product developments help customers more efficiently democratize analytics throughout their organizations while seamlessly managing analytic workloads and building SAS into a variety of applications. "Among analytics providers, SAS is a recognized leader for reimagining the way analytics and machine learning are consumed so users realize optimal results that solve business challenges faster with more accuracy," said Ritu Jyoti, Program Vice President of Artificial Intelligence Research at IDC. "This iteration of the SAS Viya platform gives users at all levels of an organization an agile, powerful advanced machine learning engine to help master the complex data that's in cloud environments." Recognizing that so many organizations have struggled with the global pandemic and its effects, SAS CEO and founder Jim Goodnight says SAS Viya can help in the toughest times. "SAS Viya helps organizations see their data, customers and operations in new ways that encourage confident decision making," said Goodnight.

Last week we announced a new strategic partnership with Microsoft to further shape the future of AI and analytics in the cloud. This commitment will make it easy for SAS customers to move their analytics workloads to the cloud. And it will introduce SAS technologies to millions of Azure customers through APIs and deeper integrations that can enhance existing applications with analytics. To help illustrate how you can use SAS on Azure, I am sharing three inspiring examples from a recent SAS hackathon. Participants in this event were challenged to solve problems related to the United Nations Global Goals for Sustainable Development using SAS Viya .

Have you heard that SAS offers a collection of new, high-performance CAS procedures that are compatible with a multi-threaded approach? The free e-book Exploring SAS Viya: Data Mining and Machine Learning is a great resource to learn more about these procedures and the features of SAS Visual Data Mining and Machine Learning. Download it today and keep reading for an excerpt from this free e-book! In SAS Studio, you can access tasks that help automate your programming so that you do not have to manually write your code. In this blog post, you will learn the syntax for two of the new, advanced data mining and machine learning procedures: PROC TEXTMINE and PROCTMSCORE.

R first appeared in 1993 and has gained a steady and fiercely loyal fan base. But as data sets become both longer and wider, storage and processing speeds become an issue. Having spent weeks whipping an extremely wide and messy data set into shape using only R, I am so grateful for SAS Viya and not having to go through that again. SAS Viya is a cloud-enabled, in-memory analytics engine which allows for rapid analytics insights. SAS Viya utilizes the SAS Cloud Analytics Services (CAS) to perform various actions and tasks.