Find out how analytics, from data mining to cognitive computing, is changing the way we do business
만약 나의 주치의가 내 디지털 트윈(Digital Twin)을 만들어 실시간으로 나의 상황을 다양한 센서 데이터 등을 통해 업데이트 받을 수 있다면 어떨까요? 현실세계의 기계나 장비, 사물 등을 컴퓨터 속 가상세계에 구현한 디지털 트윈을 통해 몸 속의 잠재적인 질병에 대한 신호를 미리 받을 수 있을지도 모릅니다. 디지털 트윈이 암 관련 질병을 미리
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の機能を使用して一般物体検出（Object Detection）を試してみました。 今回は、弊社で用意した数枚の画像データを使用して、処理の流れを確認するだけなので、精度に関しては度外視です。 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）のインポートとセッションの作成 ２．一般物体検出向け学習用データの作成 ３．モデル構造の定義 ４．モデル生成（学習） ５．物体検出（スコアリング） １．必要なパッケージ（ライブラリ）のインポートとセッションの作成 swatやdlpyなど、必要なパッケージをインポートします。 from swat import * import sys sys.path.append(dlpy_path) from dlpy.model import * from dlpy.layers import * from dlpy.applications import * from dlpy.utils import * from dlpy.images import ImageTable from dlpy.splitting import two_way_split from dlpy.blocks import *
This week I noticed that they've started building the lot where they sell Christmas trees near SAS (at the intersection of Maynard & Reedy Creek Rd). They put up a nice rustic wooden fence, and lights, and maybe even a fire pit to keep their workers warm. They sell some
A data analyst asked how to compute parameter estimates in a linear regression model when the underlying data matrix is rank deficient. This situation can occur if one of the variables in the regression is a linear combination of other variables. It also occurs when you use the GLM parameterization
은행은 금융위기와 같은 경제적 충격이 외부에서 발생했을 때 채무 불이행에 따른 손실 규모를 파악하고 보유하고 있는 위험자산에 대한 포트폴리오 변화를 빠르게 확인할 수 있어야 하는데요. 특히 글로벌 금융위기 이후 은행권을 대상으로 글로벌 경제 위기에 견딜 수 있는 재무 건전성 역량을 문서화하는 규제요구가 높아지면서 대형 투자은행들이 경제 상황이 극도로 나빠졌을 때
Data management gets lost in the enthusiasm around Artificial intelligence (AI) and machine learning (ML). Not surprising, when it's an algorithm that decides what search results to show you, guides the self-driving cars on the roads, and powers the anti-fraud bots that monitor every credit card transaction we make. Charles
Finanzdienstleister haben aktuell massive Herausforderungen beim Management ihrer Daten: Der Kostendruck zwingt einerseits zu einem hocheffizienten Betrieb („run“). Zugleich wandeln sich andererseits die Prozesse im Business, Stichwort Digitalisierung („change“). Die drückenden Regeln der Aufsicht scheinen sich nicht vereinen zu lassen mit dem Anspruch der Kunden, flexibel, fix und doch datensparsam
La duda es uno de los nombres de la inteligencia. - Borges Para data scientist/analistas de datos/viejos mineros/lobos de mar. En los comienzos de nuestra carrera de data scientists, el poder de cómputo era muy inferior al que disponemos hoy. Sin embargo, muchas empresas ya veían el enorme potencial de
Healthcare fraud is alive and well. Honesty is dead and gone. There, I’ve said it. What else are we to take from surveys that find that 27% of people would sell their work passwords...44% of them for less than $1,000?* What does it mean that 37% of survey respondents think
In my first two posts of this blog series, we heard why two students chose to pursue a STEM field and what appealed to them about data science. We also heard how they put their knowledge to work on a real-world data science project. Today, we'll hear their advice to future
There has been a lot of controversy surrounding this year's midterm election, when it comes to counting the ballots ... and I kept hearing the term provisional ballots in the news. But I'm embarrassed to say that I didn't really know much about provisional ballots. I decided to do a
When describing their business model, our customer, Epipoli (one of the leading gift card companies in Europe), tells the story of the ancient Limoncello makers of Italy. Limoncello is an intensely lemon-flavored liqueur famously produced in Sorrento, the Amalfi coast, and the island of Capri. The drink started as a local tradition, but quickly
Se promueve como el fin de semana más esperado, creado para reactivar la economía de México: el Buen Fin, que en su versión 2018 se celebra del 16 al 19 de noviembre. De acuerdo con la Secretaría de Economía (SE), se prevé que la derrama económica de este año supere
The US 'midterm' elections have finally started to wind down, and we finally have some (mostly) finalized results to study. But what's the best way to visualize who won the US congressional seats in each of the 435 districts? Let's dive into this topic!... Preparation For starters, I couldn't find
Teenagers. I have three boys, and two of them are teenagers. 15 year-old Kav is my middle son, and he gave me permission to share his story here. When he was five, Kav was diagnosed with Type I Diabetes, and I'm in awe of how he's accepted this challenging, lifelong
An ROC curve graphically summarizes the tradeoff between true positives and true negatives for a rule or model that predicts a binary response variable. An ROC curve is a parametric curve that is constructed by varying the cutpoint value at which estimated probabilities are considered to predict the binary event.
In many grocery stores throughout the country, the acronym “WIC” accompanies a number of the food items on the shelves. The letters stand for the federal “Women, Infants and Children” program that provides nutritional food to pregnant women and their young children who are in need. While this is a
Note: Today’s utility industry is in upheaval. All of the assumptions the business has run on have been turned on their heads. This post is the third in a three-part series looking at how analytics are helping utilities navigate this challenging landscape and find new opportunities for improvements in operations,
인공지능(AI)이 우리에게 미치는 영향이 나날이 커지면서 일자리를 대체할 것이라는 우려도 높아지고 있습니다. 이를 위해서 인공지능의 윤리 방안과 규제에 대한 논의가 이루어지고, 기업이 알고리즘으로 인해 일자리를 빼앗긴 직원에게 재교육을 제공해야 한다는 목소리가 나오고 있는데요. 하지만 이러한 모든 내용은 인공지능이 미치는 부정적인 면에만 치우쳐 있습니다. 그렇다면 인공지능이 우리의 삶에 주는 혜택으로는 무엇이 있을까요? 인공지능,
Joyce Norris-Montanari cites five things she considers essential to data management for analytics.
One would expect analytics in government to be a hot topic at a SAS government event. What the crowd didn't see coming was Margaret Weichert, Acting Director of the US Office of Personnel Management and Deputy Director for Management at the Office of Management and Budget, touting her ability to
Emerging technologies enable retailers to differentiate with data and analytics that enhance the customer experience. In four key ways, retailers can partner with the analytics using data associated with past and present interactions and, through systemic innovation capitalize on future customer interactions.
With the recent midterm elections here in the US, I frequently saw congressional district maps popping up in the news. And being a GraphGuy, I wanted to fully understand these maps, to see if I might could improve them. If you're interested in congressional district maps, follow along as I
Como se indica su nombre, las tiendas de conveniencia se han convertido en los puntos de venta donde los consumidores no sólo pueden adquirir muchos de los productos que requieren a diario, en el momento que lo deseen, sino también realizar pagos de servicios, abonar saldo o a sus líneas
Phil Simon chimes in with some tips on how to set these folks loose.
Will the real Pareto distribution please stand up? SAS supports three different distributions that are named "Pareto." The Wikipedia page for the Pareto distribution lists five different "Pareto" distributions, including the three that SAS supports. This article shows how to fit the two-parameter Pareto distribution in SAS and discusses the
Los avances tecnológicos, las expectativas de los clientes y las regulaciones que redefinen el mercado, han sido puntos clave para que el sector de los seguros se enfoque en el crecimiento de sus ventas, su rentabilidad y la lealtad y el cuidado de sus clientes. ¿Qué ha pasado entonces? las
Health care is facing an unprecedented need to reform, drive quality and cut costs. Growth in targeted, specific treatments and diagnostic technology, coupled with a rise in people with long-term and multiple chronic conditions, is creating unsustainable demand on the system. To thrive – or even merely survive – health
Mein Name ist Daniel und ich bin in der vierten Klasse. Diese Woche wurden die Eltern in meine Schule eingeladen, um uns etwas über ihre Arbeit zu erzählen. Und mein Vater war mit dabei. Am Anfang war ich etwas unsicher, ob ich mich darüber freuen sollte. Denn wenn sein Vortrag
SASでは、従来からオープン・AIプラットフォームであるSAS Viyaの機能をPythonから効率的に活用いただくためのハイレベルなPython向けAPIパッケージであるDLPyを提供してきました。 従来のDLPyは、Viya3.3以降のディープラーニング（CNN）と画像処理（image action set）のために作成された、Python API向けハイレベルパッケージです。 DLPyではKerasに似たAPIを提供し、より簡潔なコーディングで高度な画像処理やCNNモデリングが可能でした。 そして、この度、このDLPyが大幅に機能拡張されました。 最新版DLPy1.0では、以下の機能が拡張されています。 ■ 従来からの画像データに加え、テキスト、オーディオ、そして時系列データを解析可能 ■ 新たなAPIの提供: ・ RNN に基づくタスク: テキスト分類、テキスト生成、そして 系列ラベリング（sequence labeling） ・ 一般物体検出（Object Detection） ・ 時系列処理とモデリング ・ オーディオファイルの処理と音声認識モデル生成 ■ 事前定義ネットワーク（DenseNet, DarkNet, Inception, and Yolo）の追加 ■ データビジュアライゼーションとメタデータハンドリングの拡張 今回はこれらの拡張機能の中から「一般物体検出（Object Detection）」機能を覗いてみましょう。 SAS Viyaでは従来から画像分類（資料画像1.の左から２番目：Classification）は可能でした。例えば、画像に映っている物体が「猫」なのか「犬」なのかを認識・分類するものです。 これに加えて、DLPy1.0では、一般物体検出（資料画像1.の左から３番目：Object Detection）が可能になりました。 資料画像１. (引用：Fei-Fei Li & Justin Johnson & Serena Yeung’s Lecture
