SAS Blogs

Machine Learning

Get the latest machine learning algorithms and techniques

Rick WicklinJanuary 30, 2019 0

Model assessment and selection in machine learning

Machine learning differs from classical statistics in the way it assesses and compares competing models. In classical statistics, you use all the data to fit each model. You choose between models by using a statistic (such as AIC, AICC, SBC, ...) that measures both the goodness of fit and the

English

Analytics | Machine Learning | Programming Tips

Partition data into training, validation, and testing in SAS

Rick WicklinJanuary 21, 2019 0

Create training, validation, and test data sets in SAS

In machine learning and other model building techniques, it is common to partition a large data set into three segments: training, validation, and testing. Training data is used to fit each model. Validation data is a random sample that is used for model selection. These data are used to select

English

Artificial Intelligence | Machine Learning

Christina HsiaoJanuary 16, 2019 0

Reduce the cost-barrier of generating labeled text data for machine learning algorithms

Amidst the growing popularity of modern machine learning and deep learning techniques, one of the biggest challenges is the ability to obtain large amounts of training data suitable for your use case. This post discusses how the analytical approach for Named Entity Recognition (NER) can help.

English

Analytics | Artificial Intelligence | Data Visualization | Machine Learning | Programming Tips

Melanie CareyJanuary 14, 2019 0

How SAS Visual Analytics' automated analysis takes customer care to the next level - Part 3

In the second of three posts on using automated analysis with SAS Visual Analytics, we used the automated analysis object to get a better understanding of our variable of interest, X-Sell and Up-sell Flag, and how it is influenced by other variables in our dataset. In this third and final

English

Advanced Analytics | Artificial Intelligence | Machine Learning

Katherine TaylorJanuary 10, 2019 0

Practical AI in banking

AI seems to be mentioned everywhere these days. But how can AI be used in day-to-day work? Here, Katherine Taylor explains an example of "practical AI" in banking using SAS Visual Data Mining and Machine Learning. She'll explore more business problems and industries in future posts.

English

Analytics | Artificial Intelligence | Data Visualization | Machine Learning | Programming Tips

Melanie CareyJanuary 7, 2019 0

How SAS Visual Analytics' automated analysis takes customer care to the next level - Part 2

In the first of three posts on using automated analysis with SAS Visual Analytics, we explored a typical visualization designed to give telco customer care workers guidance on customers most receptive to upgrade their plans. While the analysis provided some insight, it lacked analytical depth -- and that increases the risk of wasting time, energy and

English

Communications

Analytics | Artificial Intelligence | Data Visualization | Machine Learning | Programming Tips

Melanie CareyJanuary 2, 2019 0

How SAS Visual Analytics' automated analysis takes customer care to the next level - Part 1

You're the operations director for a major telco's contact center. Your customer-care workers enjoy solving problems. Turning irate callers into fans makes their day. They also hate flying blind. They've been begging you for deeper insight into customer data to better serve their callers. They want to know which customers

English

Communications

Analytics | Machine Learning

Alejandro BolañosDecember 27, 2018 0

Explicate! Entendiendo los modelos de Machine Learning (Parte 3: Individual Conditional Expectation)

Parte I: Introducción Parte II: Partial Dependence Plots Repasemos como llegamos hasta acá. Desde hace varios años los algoritmos de machine learning nos ofrecen una mejora sustancial en sus capacidades, son cada vez más precisos. Además, gracias a la optimización hiperparamétrica, el analista puede utilizar el tiempo de prueba y

Spanish

Advanced Analytics | Machine Learning

Alejandro BolañosDecember 21, 2018 0

Explicate! Entendiendo los modelos de Machine Learning (Parte 2: Partial Dependence Plots)

Pueden acceder a la parte I de esta serie de artículos en este link. Antes de continuar donde dejamos el artículo anterior, veamos un artículo publicado hace unos días que tiene ver con nuestro tópico: How Important is that Machine Learning Model be Understandable? We analyze poll results. Este artículo

Spanish

Analytics | Artificial Intelligence | Internet of Things | Machine Learning

Javier Alexander RengifoDecember 21, 2018 0

El análisis predictivo: impactando los negocios y sus procesos de transformación digital

La tecnología y la sociedad están evolucionando en un entorno digital que exige cambios en el modelo de negocio, la infraestructura y la cultura de una organización. Sin embargo, uno de los mayores retos a los que se están enfrentando las empresas en este momento se basa en el desconocimiento

Spanish

Communications | Education

Advanced Analytics | Machine Learning

SAS KoreaDecember 21, 2018 0

딥러닝을 활용한 객체 탐지 알고리즘 이해하기

Korean

Analytics | Artificial Intelligence | Internet of Things | Machine Learning

Bryan SaundersDecember 20, 2018 0

AIoT helps move transportation forward

By now, we're all aware of the seismic shift occurring across industries as a result of the Internet of Things. But do we all see the changes in the same light? From where I sit, there's still a wide gap in viewpoints and perspectives. In its simplest form, we often

English

Insurance | Travel

Internet of Things | Machine Learning

Christian GoßlerDecember 19, 2018 0

Lenin jagt Dr. Noh ohne Daten im Internet of Tuna (IoT7)

Lenin hebt sein Glas: „Auf unsere digitalisierte Service-Flotte und das zehnte angebundene Werk!“ Ich proste zurück: „Auf Ihren neuen Job!“ – „Ach, ich mache das Gleiche wie vorher: Machine Learning – insbesondere für das Internet of Things …“ Der Kellner unterbricht: „Wer wollte noch Thunfisch-Nigiri?“ – „Internet of Thunfisch“, lacht

German

Manufacturing

Analytics | Data Management | Learn SAS | Machine Learning

Michael HerrmannDecember 17, 2018 0

DevOps & SAS: Entwicklung und Betrieb aus einer Hand?

K(o)ennen Sie schon „DevOps“? Machen Sie SAS? Dann lohnt sich eventuell ein frischer Blick auf die Kombination! Denn immer mehr Unternehmen probieren, ihren produktiven Betrieb auch in die Hände der Software-Entwickler zu legen (2 von 3 laut Jenkins) – speziell in der Analyse, insbesondere beim agilen Modellieren und dem Veredeln

German

Artificial Intelligence | Fraud & Security Intelligence | Machine Learning

SAS KoreaDecember 13, 2018 0

사기 탐지부터 방지까지, 인공지능과 머신러닝이 해결할 수 있는 범위는?

Korean

Advanced Analytics | Learn SAS | Machine Learning

SAS KoreaDecember 10, 2018 0

머신러닝 해석력 시리즈 4탄: 라임(LIME)으로 모델 해석력 개선하기!

Korean

Advanced Analytics | Analytics | Customer Intelligence | Data Visualization | Machine Learning

Suneel GroverDecember 6, 2018 0

SAS Customer Intelligence 360: Decision management, machine learning, and digital marketing

A typical day brings countless business decisions that affect everything from profitability to customer experience. What is a reasonable price point? Which audience segments should I personalize offers for? When should I recommend specific content earlier in a customer journey? Daily decisions like these can alter the trajectory of a

English

Artificial Intelligence | Machine Learning

Innovation - how curiosity and criticism

Antonio AutorinoNovember 30, 2018 0

Intuito e curiosità come driver per la creazione di nuovi significati

Incontrare Roberto Verganti in occasione di Analytics Experience 2018 è stata una grande emozione. E' un enorme piacere ascoltare dal vivo questo professore del Politecnico di Milano, che dal palco trasmette la stessa energia che ritroviamo nei suoi libri. Ho sentito parlare per la prima volta di lui nel 2010 quando

Italian

Advanced Analytics | Customer Intelligence | Machine Learning

SAS KoreaNovember 30, 2018 0

SAS 커스터머 인텔리전스 360(SAS Customer Intelligence 360): 블랙 박스 모델의 해석 기법 알아보기

Korean

Artificial Intelligence | Learn SAS | Machine Learning | SAS Events

Charu ShankarNovember 28, 2018 0

3 things you need to know about SAS Global Forum 2019 from the conference chair

Find out what SAS Global Forum 2019 conference chair MaryAnne DePesquo says about the upcoming conference in Dallas.

English

Artificial Intelligence | Machine Learning

Antonio AutorinoNovember 27, 2018 0

How curiosity and criticism drive the generation of new meanings

Listening to Roberto Verganti at Analytics Experience 2018 was a great experience. It is an enormous pleasure to watch this professor from Milan Polytechnic, who transmits the same energy in person that he puts into his books. I first came across him in 2010, when thanks to SAS, I took

English

Advanced Analytics | Analytics | Customer Intelligence | Data Visualization | Machine Learning

Suneel GroverNovember 27, 2018 0

SAS Customer Intelligence 360: Model management for competitive differentiation [Part 1]

The universe of customer experiences, digital analytics, personalization and decisioning is massive. At times, it can seem as complicated and vast as the galaxy itself. With intricate subjects underneath this umbrella, you can lose direction, wander aimlessly, or feel a misleading sense of success or failure. When you lose vision,

English

Advanced Analytics | Customer Intelligence | Machine Learning

SAS KoreaNovember 27, 2018 0

SAS 커스터머 인텔리전스 360(SAS Customer Intelligence 360): 블랙 박스 모델의 해석력 이해하기

Korean

Analytics | Machine Learning

Chris HartmannNovember 22, 2018 0

Machine Learning: Mehr Effizienz im Planungsprozess

Sie glauben, dass Machine Learning die Rolle von Nachfrageplanern komplett ersetzen kann? Dann lesen Sie diesen Beitrag besser nicht. Wenn Sie jedoch der Ansicht sind, dass maschinelles Lernen den Planungsprozess automatisieren kann, so dass Nachfrageplaner effizienter arbeiten können, dann stimme ich Ihnen voll und ganz zu! Intelligente Automatisierungstechniken sind quasi

German

Manufacturing

Analytics | Artificial Intelligence | Machine Learning

Makoto Unemi (畝見真)November 21, 2018 0

SAS Viya：一般物体検出（Object Detection）を試してみた

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 *

Japanese

Advanced Analytics | Artificial Intelligence | Machine Learning

Xindian LongNovember 19, 2018 0

Understanding object detection in deep learning

What is object detection? Object detection, a subset of computer vision, is an automated method for locating interesting objects in an image with respect to the background. For example, Figure 1 shows two images with objects in the foreground. There is a bird in the left image, while there is a dog

English

Advanced Analytics | Customer Intelligence | Machine Learning

SAS KoreaNovember 19, 2018 0

SAS 커스터머 인텔리전스 360(SAS Customer Intelligence 360): 머신러닝의 블랙 박스 모델이란?

Korean

Artificial Intelligence | Customer Intelligence | Machine Learning

Jeanne (Hyunjin) ByunNovember 16, 2018 0

기업 성공 사례에서 인공지능(AI)의 혁신적인 역할을 살펴보다!

Korean

Suneel GroverNovember 9, 2018 0

SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 3]

In parts one and two of this blog posting series, we introduced machine learning models and the complexity that comes along with their extraordinary predictive abilities. Following this, we defined interpretability within machine learning, made the case for why we need it, and where it applies. In part three of

English

Artificial Intelligence | Machine Learning

SAS KoreaNovember 6, 2018 0

인공지능(AI)이 재정의하는 윤리는? 윤리적인 인공지능 시스템 관리를 위한 4가지 핵심요소

Korean

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