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
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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
We have updated our software for improved interpretability since this post was written. For the latest on this topic, read our new series on model-agnostic interpretability. While some machine learning models – like decision trees – are transparent, the majority of models used today – like deep neural networks, random forests, gradient boosting
Artificial intelligence often seems misunderstood, especially in fraud. The same is true of machine learning. One of the amazing things about them is they ask the unasked questions. This occurs as artificial intelligence (AI) and machine learning (ML) go about their daily work. So, what is the unasked question? Too
President Donald Trump - people seem to either love him or hate him. Which makes for an interesting data-analysis topic ... tracking Trump's approval rating. Follow along as I explore some data! I'll start with what I consider the 'best' approval-rating graph I've found so far. Here's a screen-capture of
Jim Harris says people still play a pivotal role in data-driven decision making.
What skills will students need in order to pursue a lucrative career in analytics? I recently interviewed two professors to find out. In my first post, the professors discussed the importance of teaching and learning analytics. Today, we'll hear their top advice for students studying analytics, such as: get a
A useful feature in PROC SGPLOT is the ability to easily visualize subgroups of data. Most statements in the SGPLOT procedure support a GROUP= option that enables you to overlay plots of subgroups. When you use the GROUP= option, observations are assigned attributes (colors, line patterns, symbols, ...) that indicate
Vor ein paar Wochen hat das erste deutsche SAS User Group Meetup in Berlin stattgefunden. Dort hatte ich die Gelegenheit, mit Igor Khorlo, Senior Statistical Programmer bei Syneos Health Deutschland und Gründer der SAS User Group Germany (SUGG), über seine Motivation zu sprechen, die Gruppe ins Leben zu rufen –
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 second in a three-part series looking at how analytics are helping utilities navigate this challenging landscape and find new opportunities for improvements in operations,
FRTB(Fundamental review of the trading book)는 은행의 시장 리스크 관리 방식을 바꿀 것입니다. 바젤은행감독위원회(BCBS)가 FRTB를 발표하고 이 기준에 따라 전세계적으로 시장 리스크를 측정해 공시하도록 한 것인데요. 대다수 은행은 2020년 12월 데드라인과 바뀌고 있는 요구 사항을 보며 ‘기다려야 한다’는 결론을 내리고 있지만, 그저 기다리기만 하는 것은 위험한 전략이 될 수 있습니다. 금융
I’m on day 8 of my 10 day sabbatical from running. By day 3, I already felt anxious about not lacing up my shoes and heading out to feel the wind in my face, never mind the fact that I was still exhausted and sore from the previous week’s races.
GAHHHHHHHHH! My screams filled the office hallways on a Sunday afternoon. In agony, I hopped to the ice machine to find relief for my crushed toe. Moments before, while hanging my shiny new patent plaque on the wall, it dropped six feet and landed on my big toe joint. Since
Erst kürzlich habe ich mich mit Thomas Gartzen, Geschäftsführer des European 4.0 Transformation Center, unterhalten. Dabei ging es neben Innovation Labs auch um Change Management und darum, wie sich ein analytischer Ansatz in Unternehmen umsetzen lässt. Andreas Gödde: Thomas, kann man sagen, dass jetzt alle Unternehmen Softwareunternehmen sind? Thomas Gartzen:
If you want to bootstrap the parameters in a statistical regression model, you have two primary choices. The first, case resampling, is discussed in a previous article. This article describes the second choice, which is resampling residuals (also called model-based resampling). This article shows how to implement residual resampling in
음식, 패션, 그리고 풍부한 문화유산으로 유명한 이탈리아의 경제 중심 밀라노는 오랜 역사를 바탕으로 개방과 혁신이 공존하는 ‘인큐베이터’ 도시인데요. 이탈리아에서 기술의 발전을 이끌고 있는 밀라노에서 10월 22일부터 24일까지 사흘간 유럽 최대 규모의 분석 컨퍼런스 ‘SAS 애널리틱스 익스피리언스(Analytics Experience) 2018'가 개최됐습니다. 이번 SAS 애널리틱스 익스피리언스에는 1,200명 이상의 전 세계 산업별 비즈니스 리더와 분석
The other day I was playing around with the voter registration data for all ~8 million registered voters in North Carolina (yes - this guy knows how to have fun!), and I got to wondering what last names were the most common. I summarized the data by county, and the
How should a data trust process work? David Loshin elaborates.
기업의 마케팅 전략도 인공지능(AI), 사물인터넷(IoT)과 같은 혁신적인 기술이 등장하며 함께 발전하고 있습니다. 고객 중심의 IT 환경에서 많은 기업은 높은 고객 충성도를 달성하고자 고객 여정(customer journey) 최적화에 많은 노력을 기울이고 있는데요. 인공지능 역시 고객 여정을 최적화하기 위한 기술로 많은 비즈니스에 도입되고 있습니다. 인공지능 강화학습(Reinforcement learning) 모델을 적용한 대표적인 예로는 미국 게임 개발사 아타리(Atari)가 선보인
If you want to bootstrap the parameters in a statistical regression model, you have two primary choices. The first is case resampling, which is also called resampling observations or resampling pairs. In case resampling, you create the bootstrap sample by randomly selecting observations (with replacement) from the original data. The
In my 15+ years working in clinical research, I've not seen significant evolution in the way we do clinical trials and apply advanced analytics to clinical trial data. A personal story demonstrates that a similar problem is at play in health care. Each year my daughter visits the children’s cardiology
This past Sunday was the last day of the NC State Fair, and we broke some records this year! Can you guess what those records were? I'll ramble on about the fair to give you time to come up with your guess, and then I'll let you know about the
I've been recovering for 15 years now, after a lengthy career caring for critically ill patients. Now, I’m part of a team at SAS that’s working to transform health care – and that's important to me because of something that happened when I was an ICU nurse. It changed my
Applying machine learning approaches to forecasting is an area of great research interest. Progress is being made on multiple fronts, for example: In the M4 Forecasting Competition, completed earlier this year, the top two performers utilized machine learning with traditional time series forecasting methods. At the link you'll find full
Innovation Labs gibt es schon seit einiger Zeit in allen Varianten. Einige gehören zu großen Unternehmen, andere zu Forschungsinstituten. Die RWTH Aachen hat ein solches Innovation Lab, das European 4.0 Transformation Center (E4TC), ins Leben gerufen und sucht Unternehmen, die sich daran beteiligen. Wie genau ein solches Innovation Lab funktioniert,
Have you noticed a lot of graphs popping up lately, about politicians, voters, and elections? ... Well of course - it's an election year! If you follow my blog posts, then you're probably a bit "smarter than the average bear" when it comes to scrutinizing graphs. And election graphs election
올해 초 2018년과 미래를 관통할 두 가지 기술로 '인공지능(AI)’과 ‘자동화(Automation)'를 소개해 드렸는데요. 인공지능과 자동화 기술은 사물인터넷(IoT)과 어떻게 연결될 수 있을까요? IDC 퓨처스케이프(IDC FutureScape)가 발표한 ‘2017년 전 세계 IoT 전망’ 보고서에 따르면, 2019년까지 사물인터넷에서 생성된 데이터의 40% 이상이 네트워크 엣지(edge)에 저장되어 처리되고 분석될 전망입니다. 또한 효과적인 사물인터넷 기술은 스트리밍 분석과 머신러닝을 결합해 진행될
A SAS programmer asked how to rearrange elements of a matrix. The rearrangement he wanted was rather complicated: certain blocks of data needed to move relative to other blocks, but the values within each block were to remain unchanged. It turned out that the mathematical operation he needed is called