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Each day, more than 130 Americans die from opioid overdoses. Combating the opioid epidemic begins with understanding it, and that begins with data. SAS recently partnered with graduate students from Carnegie Mellon University (CMU) 's Heinz College of Information Systems and Public Policy to understand how data mining and machine
Each week in February, your Work/Life team has invited therapists and dating professionals in the community to respond to questions about relationships. To kick off this series, we asked our experts… How do you keep from losing yourself in a relationship—new or longstanding? Kate Freiman-Fox, Ph.D. Matchmaking, Date and Relationship
February may be a short month, but it's packed: Groundhog Day, the Super Bowl, Valentine's Day...and the flu. Flu season is a lot like watching a sunrise. When flu season begins each Oct 1 there is a great sense of anticipation as the HCC administers thousands of flu shots and begins reporting flu and influenza-type illnesses to
Recently, I worked on a cybersecurity project that entailed processing a staggering number of raw text files about web traffic. Millions of rows had to be read and parsed to extract variable values. The problem was complicated by the varying records composition. Each external raw file was a collection of
Im vorangegangenen Blog habe ich die „vier Säulen des Vertrauens“ für automatisierte Entscheidungen vorgestellt. Dieser hat gezeigt: Erklärbarkeit und Transparenz beziehen sich auf den gesamten analytischen Prozess. Wie sieht es aber mit der „Blackbox“ der maschinellen Lernalgorithmen aus? Auch dort muss Transparenz durch eine analytische Plattform gewährleistet sein. Die gute
Feature generation (also known as feature creation) is the process of creating new features to use for training machine learning models. This article focuses on regression models. The new features (which statisticians call variables) are typically nonlinear transformations of existing variables or combinations of two or more existing variables. This
Lenin schaut übellaunig wie ein Bolschewik: „Sherlock? Der hat mit leistungsfähiger künstlicher Intelligenz so wenig zu tun wie mit echter Detektivarbeit! Wir brauchen weder Sherlock noch seinen Doktor!“ Lenin hatte mich zum Challenger Workshop eingeladen. Ein Berater der Accelerator Change & Disruption Consultancy (AC&DC) bat nach kurzem Impulsvortrag (Change! Disruption!)
Talk to most parents about their role as parent, and you eventually hear the parent sigh and say, “I just want my kid to be happy,” or “A parent is only as happy as their least happy child.” There was a time in my life when I nodded in agreement,
SAS Press author Matt Windham shows you how to use the SAS procedure PROC HTTP to grab raw data from a website.
In the previous Graphically Speaking blog for PROC SGMAP, you used PROC GPROJECT so map regions would match OpenStreetMap and Esri background images. This time, the same British Columbia shapefile is used with: PROC GREMOVE to remove unwanted boundary lines PROC GREDUCE to reduce map data PROC GPROJECT to zoom
Recently, I was given an amazing opportunity to work on a project in biomedical image analytics in collaboration with a large university medical center. The goal of the project was to develop a computer vision system that identifies tumors in CT scans of livers. I have always loved applying technology
As a SAS analytical software tester, Portia Exum knows what it takes to deliver quality software. She understands the rigor and the dedication to produce a product that the world can trust. But last year, she was on the receiving end of what it means to trust and find confidence
One of the key health trends we’ll continue to follow in 2019 is the flood of medical and personal data that, if managed and analyzed properly, could help health care organizations provide better care, life sciences companies deliver better therapies and individuals make smarter lifestyle choices. Sounds great, but there
Im vorangegangenen Blogbeitrag bin ich darauf eingegangen, welchen geschäftlichen Nutzen die IFRS-9-Umsetzung für Banken haben kann – abgesehen davon, die Aufsichtsbehörden zufriedenzustellen. Die gleiche Frage stellt sich Versicherern vor dem Hintergrund von IFRS 17. Bis vor Kurzem war die Bilanzierung von Versicherungsverträgen denkbar einfach. Die meisten Accounting-Standards erfordern keine speziellen
I previously discussed how you can use validation data to choose between a set of competing regression models. In that article, I manually evaluated seven models for a continuous response on the training data and manually chose the model that gave the best predictions for the validation data. Fortunately, SAS