When you go to the grocery store, you see that items of a similar nature are displayed nearby to each other. When you organize the clothes in your closet, you put similar items together (e.g. shirts in one section, pants in another). Every personal organizing tip on the web to
SAS Global Forum 2016のユーザープログラムでの発表論文を、”Machine Learning”というキーワードで検索し、機械学習関連の論文を集めてみました。 SAS Global Forum 2016 Proceedings - Machine Learning 関連のユーザーやパートナーによる講演・論文 Turning Machine Learning Into Actionable Insights 機械学習=意思決定プロセスの自動化 PROC IMSTAT Boosts Knowledge Discovery in Big Databases (KDBD) in a Pharmaceutical Company 日本の塩野義製薬様の機械学習への取り組み Diagnosing Obstructive Sleep Apnea: Using Predictive Analytics Based on Wavelet Analysis in SAS/IML®
SAS Global Forum 2016のユーザープログラムでの発表論文を、"Machine Learning"というキーワードで検索し、機械学習関連の論文を集めてみました。 SAS Global Forum 2016 Proceedings - Machine Learning 関連のSAS社員による講演・論文 Best Practices for Machine Learning Applications 機械学習の実践において一般的に遭遇する課題と解決のためのガイドラインを提供します。機械学習について初心者の方は、こちらもご活用ください⇒SASジャパン機械学習ページへ An Efficient Pattern Recognition Approach with Applications BASE SASおよびSAS Enterprise Minerを使用した、教師あり/なしタイプのパターン認識（画像認識）テクニックの紹介。パターン認識に関しては、この発表者の一人、Patrick Hallがウェビナーで他の例で解説しておりますので、そちらもあわせてご覧ください⇒「機械学習とディープ・ラーニング」ウェビナー Mass-Scale, Automated Machine Learning and Model Deployment Using SAS® Factory Miner and SAS® Decision Manager よりマイクロセグメント化するビジネス課題の解決のための自動化された機械学習製品の紹介 Streaming
Research indicates that IoT and Machine Learning are more valuable to utilities when used in combination but there are hurdles to overcome first. Machine learning and IoT will enable utilities to better realize the next generation of the power grid: a distributed system with power flows among millions of things
If I were to show you a picture of a house, you would know it’s a house without even stopping to think about it. Because you have seen hundreds of different types of houses, your brain has come to recognize the features – a roof, a door, windows, a front
Machen wir doch gemeinsam eine kleine Zeitreise in die Zukunft. Es ist Freitag, der 29. April 2016, der Tag nach der größten Konferenz für Business Intelligence im deutschsprachigen Raum, dem SAS Forum Deutschland. Und wir lauschen dem Bericht zweier Teilnehmer des SAS Forum Deutschland, die sich über die Highlights des
How comfortable are you with hard decisions? If it affected you, how comfortable would you be with losing your agency and having someone else make the decision for you? What if that decision isn’t made by a person but a machine? More than abstract questions, these are going to become
Machine learning is not new. SAS has been doing it for over 20 years and some early machine learning papers date back to the 50’s. So why is it one of the hottest topics at the Strata Hadoop World conference later this week? Clearly, Hadoop is playing a major role
Lately there seems to be a surge in the term machine learning. Much like big data a few years ago, machine learning is the new buzzword -- and the two terms actually go hand in hand. With increasing volumes of data now stored in distributed environments such as Hadoop, it's
You’ve likely heard the news that the Google DeepMind “AlphaGo” computer not only beat a human expert at the game of Go, defeating the European Go champion, Fan Hui in five straight games, but also beat the reigning world champion grandmaster, South Korea’s Lee Sedol, 4 games to 1. Go
When the likes of Elon Musk and Stephen Hawking go on record warning about the dangers of AI, it’s probably prudent to take notice. However, before rushing off into full panic mode, some definitions and perspective would be in order. The type of artificial intelligence Musk and Hawking are referring
Is cognitive computing an application of text mining? If you have asked this question, you are not alone. In fact, lately I have heard it quite often. So what is cognitive computing, really? A cognitive computing system, as stated by Dr. John E. Kelly III, is one that has the
Hi, there! First of all, let me introduce myself, as this is my first blog. I am Simran Bagga, and three weeks ago I became the Product Manager for Text Analytics at SAS. This role might be new to me, but text analytics is not. For the past 12 years,
Health care is undergoing exponential change, and this year we’ll continue to see the industry launch bold missions to improve the patient experience. With new types of data and technologies, the vision of making health care more personalized and proactive is becoming closer to reality. In my new book “The
Health care is undergoing exponential change, and this year we’ll continue to see the industry launch bold missions to improve the patient experience. With new types of data and technologies, the vision of making health care more personalized and proactive is becoming closer to reality. In my new book “The
As an economist, I started at SAS with a disadvantage when it comes to predictive modeling. After all, like most economists, I was taught how to estimate marginal effects of various programs, or treatment effects, with non-experimental data. We use a variety of identification assumptions and quasi-experiments to make causal
In today’s world of instant gratification, consumers want – and expect – immediate answers to their questions. Quite often, that help comes in the form of a live chat session with a customer service agent. The logs from these chats provide a unique analysis opportunity. Like a call center transcript,
My view of the world is shaped by where I stand, but from this spot the future of analytics for 2016 looks pretty exciting! Analytics has never been more needed or interesting. Machine learning established in the enterprise Machine learning dates back to at least 1950 but until recently has
Can pattern recognition software tell us if it is a Hermit Thrush or a Swainson's Thrush we've seen? A few of us have been debating an identification question at work, because we agreed to help Fulbright Scholar and Duke University PhD student Natalia Ocampo-Peñuela with research she is doing related to bird collisions with windows. A sad
On the first day of Big Data Analytics my colleagues sent to me: A data scientist discussing a decision tree On the second day of Big Data Analytics my colleagues sent to me: Two business analysts and A data scientist discussing a decision tree On the third day of Big Data Analytics my
Having a mentor is the number one factor in increasing the steepness of your personal learning curve. So says my oldest, Garik, a Park Scholar at North Carolina State University (class of 2012), during a discussion he recently had with the incoming Park Scholar class of 2019. To accept the
If you turned in for my recent webinar, Machine Learning: Principles and Practice, you may have heard me talking about some of my favorite machine learning resources, including recent white papers and some classic studies. As I mentioned in the webinar, machine learning is not new. SAS has been pursuing
Have you been in your attic lately? Or maybe cleaned out that closet that all of your “stuff” seems to gravitate to? Sure, mostly you’ll just find old junk that is no longer useful or purely nostalgic, but every once in a while you come across those long lost treasures
Imagine you're an investigator sorting through 6,000 mug shots taken at different jails around the state. You are tasked with finding all the mug shots of a high-profile con artist who has been arrested in multiple cities using a number of different aliases over the last five years. How can
Even though the first papers in machine learning were in the 1950s, one could argue it goes back further to the work of Alan Turing and other early computer scientists. So why has this way of modeling seemingly become so popular now? Because data has become a commodity. Large amounts of many different
The benefits of big data often depend on taming unstructured data. However, in international contexts, customer comments, employee notes, external websites, and the social media labyrinth are not exclusively written in English, or any single language for that matter. The Tower of Babel lives and it is in your unstructured
When I ask people what they know about Denmark they often mention Hans Christian Andersen. He was born in Denmark in 1805 and is one of the most adored children’s authors of all time. Many of his fairy tales are known worldwide as they have been translated into more than
You may not be in London on October 7 to take advantage of the Lancaster Centre for Forecasting's free workshop on promotional forecasting. However, there are still plenty of forecasting educational opportunities coming up this fall: SAS Business Knowledge Series Best Practices in Demand-Driven Forecasting (Chicago, September 24-25) My colleague
Machine learning is all about automating the development process for analytical models. One way to extend the use of machine learning is to broaden your library of machine learning algorithms. Another way is to scale your machine learning process by reducing the time required to process machine learning algorithms on
Machine learning is moving into the mainstream. Once the sole purview of academic researchers and advanced technology firms, machine learning is now being is used by many companies in more traditional industry verticals. Machine learning uses mathematical (not necessarily statistical) models to learn about data. In this context, learning about
