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Todd Wright shares results of a SAS survey about consumers' data privacy concerns.
Before the Thanksgiving holiday break, I shared a graphic with our parent listserv at SAS from 11th Principle: Consent!. This graphic urges parents not to force their kids to hug relatives (or anyone) as a way to teach body safety and the concept of consent. I received so many emails
Wien und die Donau: Zahlreiche Lieder, Geschichten und Filme dokumentieren die innige Beziehung zwischen der österreichischen Hauptstadt und „ihrem“ Fluss. Das war aber nicht immer so: Über Jahrhunderte stellte das Gewässer eine große Bedrohung für die Stadt dar – und es erforderte beträchtliche Ingenieurskunst, um die Donauauen in ein echtes
Dass IFRS 9 spürbare Herausforderungen im Hinblick auf die Implementierung bringen würde, war von Anfang an klar. Neben den technischen Hürden haben sich Banken schon in einem sehr frühen Stadium den strengen Prüfungen durch Regulatoren, Investoren und Rating-Agenturen, Aufsichtsräten sowie externen und internen Prüfern stellen müssen. Doch verantwortungsbewusste und weitsichtige
PythonからSAS Viyaの機能を利用するための基本パッケージであるSWATと、よりハイレベルなPython向けAPIパッケージであるDLPyを使用して、Jupyter NotebookからPythonでSAS Viyaのディープラーニング機能を使用した時系列予測を試してみました。 大まかな処理の流れは以下の通りです。 １．必要なパッケージ（ライブラリ）のインポート ２．Sin波データの生成 ３．セッションの作成 ４．RNN向け時系列データセットの作成 ５．モデル構造の定義 ６．モデル生成（学習） ７．予測 １．必要なパッケージ（ライブラリ）のインポート swatやdlpyなど、必要なパッケージをインポートします。 import numpy as np import pandas as pd import matplotlib.pyplot as plt import swat.cas.datamsghandlers as dmh from swat import * import dlpy from dlpy import Sequential from dlpy.layers import * from dlpy.model import Optimizer, AdamSolver, Sequence
그 동안 머신러닝 해석력 시리즈를 통해서 머신러닝의 부분 의존성(PD; Partial Dependence), 데이터 세트 해석 등을 소개해드렸는데요. 오늘은 라임(LIME; Local Interpretable Model-Agnostic Explanation)을 통해 머신러닝 모델의 해석력을 개선할 수 있는 방법에 대해서 알아보겠습니다. 머신러닝 모델 해석력 시리즈 1탄, 2탄, 3탄을 놓치셨다면 아래 링크를 통해 확인해주세요! 머신러닝 해석력 시리즈 1탄: 인공지능(AI)과 머신러닝을 신뢰하기 위한 필수
While support.sas.com remains the holy grail of SAS support resources, there are so many good choices, it can sometimes be hard to know where to start. That’s why we’ve put together a new guide to make things easier for new SAS users: the SAS Starter Kit.
Sometimes, during my day-to-day job, I get to experience some really fun and unique things. I’m thankful that these experiences, while work-related, sometimes spark deeper reflection about the world around me. Case in point: a few weeks ago, I zipped into a bee suit to tour and learn about SAS’
The best way to spread Christmas cheer is singing loud for all to hear! -Buddy in Elf In the Christmas movie Elf (2003), Jovie (played by Zooey Deschanel) must "spread Christmas cheer" to help Santa. She chooses to sing "Santa Claus is coming to town," and soon all of New
La llegada de la Cuarta Revolución Industrial ha significado una ruptura de paradigmas en los diferentes sectores de la economía, no solo porque se ha traducido en el nacimiento de empresas con core digital capaces de repensar las industrias en las que operan, sino porque también tiene mucho que ver con
The SAS 9.4M6 software includes a new SGPIE procedure (preproduction) as introduced in the recent article - The SGPIE Procedure. In that article, I described the basic features of the two statements supported in the procedure, the PIE and the DONUT, with some examples. It is my humble opinion that
Once again, I have chosen to take a traditional Christmas song or carol and create a fun technology-related version of it to share with you. This is the fifth year and the eighth song, so I hope you enjoy your 2018 holiday song. Grandma got over run by a neural
Phil Simon chimes in on the increasingly important topic of data literacy.
There is one equation every retail store, call center, traffic, airport or hospital manager should know by heart. No, it’s not E = mc². The one I had in mind is this: W = 1 / (μ – λ) It may not look like much, but it can mean the
After almost 32 years, I am retiring from SAS.