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As we bid farewell to another successful SAS Explore, let’s reflect on the exciting announcements made during the Day Three general session in Las Vegas. Jared Peterson, SAS Senior Vice President of Research and Development, set the stage for a closing session focused solely on our users and customers. We
As the sun rose over the vibrant city of Las Vegas, day two of SAS Explore unfolded with a promise of even more excitement and innovation. After an electrifying Day One, there was palpable anticipation for what Day Two had in store. Host Jared Peterson stood center stage and welcomed
No creo que ninguno de los lectores de este post llegue a sorprenderse si les contamos que en SAS estamos al 100% comprometidos con el mundo académico. No obstante, hace casi medio siglo que nuestra compañía nació precisamente en las aulas de una universidad, la de Carolina del Norte. Desde
September is National Yoga Awareness Month in the U.S. Though many people are most familiar with yoga’s physical practice involving poses and breathwork, this two-part blog series focuses on its more introspective limbs.
I don't often use the SG annotation facility in SAS for adding annotations to statistical graphics, but when I do, I enjoy the convenience of the SG annotation macros. I can never remember the details of the SG annotation commands, but I know that the SG annotation macros will create
This year, Las Vegas played host to SAS Explore, an incredible gathering of developers, data scientists, engineers, programmers and more. In true Las Vegas fashion, the opening session brought all the glitz, immersing attendees in everything SAS offers. With a particular focus on SAS enthusiasts and users, day one featured exciting
Embracing AI is wonderful. From a practical business perspective, though, there are limits. This issue is broader than AI. However, I’ll constrain the conversation to that for now, given the attention AI is getting these days. Yes, some processes are undoubtedly good candidates for automation, but avoiding “technocentrism” is critical to
When I started my career as an actuarial student in the early 2000s, being successful required a good actuarial exam passing rate and good modeling skills in Visual Basic for Applications (VBA) or using SAS® to code. However, just as SAS never stands still in data analytics, the skillsets required for
La historia empresarial en Colombia está llena de anécdotas como las de uno de los grandes líderes del país que llevaba la contabilidad de sus primeras tiendas con recibos hechos a mano que colgaba en una cuerda con ganchos de ropa para que no se le perdieran. Eran tiempos lejanos
In an increasingly interconnected world, geopolitical events in one region can cause a ripple effect across global supply chains. Due to technical complexity and the concentration of large manufacturers in the Asia Pacific region, the semiconductor supply chain is especially vulnerable to disruptions. In fact, more than 65% of the
Many SAS procedures support a BY statement that enables you to perform an analysis for each unique value of a BY-group variable. The SAS IML language does not support a BY statement, but you can program a loop that iterates over all BY groups. You can emulate BY-group processing by
AI has captured the general public's imagination, so it was no surprise that it was nearly the only topic of conversation among data professionals at this year’s Chief Data and Analytics Officer (CDAO) conference in London. Of course, AI and machine learning are not new concepts for those working in
컴퓨터가 인간보다 잘 하는 몇 가지 분야가 있는데, 그 중 하나가 바로 이미지 인식입니다. 2012년 알렉스넷이 개발된 이후 컴퓨터 비전 분야는 급속도로 성장하여 우리 일상에 자연스럽게 스며들었습니다. 오늘 포스팅에서는 컴퓨터가 이미지를 어떻게 인식할 수 있는지 이론을 중심으로 살펴보도록 하겠습니다. 1. 컴퓨터 비전의 과거 우리가 모니터를 통해 바라보는 이미지의 구조부터 알아보겠습니다.
Debido a la complejidad y cambios en el mercado, las organizaciones de todo el mundo están aprovechando las oportunidades para hacer mejores predicciones, identificar soluciones y dar pasos estratégicos y proactivos, lo que significa que dependen cada vez más de los big data. Sin embargo, en su búsqueda de resistencia
Computer vision is a field of artificial intelligence that teaches computers to understand visuals. Using digital images from cameras and videos and deep learning models, machines can learn to recognize and categorize objects and respond to their surroundings based on what they “see.” Computer vision's accuracy has skyrocketed in the