This resource is designed primarily for beginner to intermediate data scientists or analysts who are interested in identifying and applying machine learning algorithms to address the problems of their interest. A typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is “which algorithm should
Where do your data scientists sit? Perhaps they occupy a typically gloomy, computer-filled basement. Or maybe they have a glassy building all to themselves. Either way, you’ll not always see business decision makers walking the same corridors. After all, analytics is best left to the experts, isn’t it? Yet back
In my last blog post, I talked about the importance of establishing the right team for data science projects. Here, I’m going to talk about some of the barriers that can prevent successful adoption of data science. Lack of strategy definition Data scientists tend to work on loosely defined business
You’ve finally done it. You managed to stay awake through the endless series of MOOC videos, and you’ve mastered the IRIS data set. You've learned that lm() will build you a pretty nifty model in R, and you can fit a Classifier with SciKit Learn. You know your Neural Net
El tema del empleo es sin duda un gran desafío que enfrentan los países en este momento. Colombia, según datos de la OCDE, es el país de esta organización con el índice de desempleo más alto: cercano al 20% a nivel nacional. Según esa entidad, con respecto a lo que
SAS has always believed in the power of education, but in today’s data-driven economy, it’s more important than ever to ensure our students are introduced to data science at an early age. We as a company are focusing our resources on creating student experiences in data literacy, computer science and
A prima vista, potrebbe sembrare che data science e psicologia abbiano ben poco in comune. Tuttavia, di recente ho iniziato ad appassionarmi di psicologia e penso che tra le due ci siano molte più somiglianze di quanto si possa pensare. 1. Sia Data Science che psicologia ci aiutano a rispondere
Teknoloji dur durak tanımıyor, günbegün yeni buluşlarla, atılımlarla ve daha nicesiyle tanışıyoruz. Daha da önemlisi, bunu artık anlık olarak yapıyoruz. İnternet çağının katkılarıyla, Türkiye’de yaşayan bir kişi dünyanın herhangi bir yerinde, dün yapılmış bir çalışmayı hemen kişisel bilgisayarının rahatlığıyla okuyabiliyor. Tabii ki, bu kadar hızlı gelişmenin artıları olurken eksileri de
A evolução do analytics e da ciência de dados gera constantes atualizações e transformações nas plataformas de análises. Este artigo tem o propósito de apresentar como o SAS tem acompanhado essa evolução. Ambiente Integrado: uma única plataforma, diversas tarefas O SAS oferece recursos que permitem acessar, explorar, transformar, analisar e
Últimamente se habla mucho de la importancia del storytelling en analytics. Obviamente, no tiene sentido analizar datos si las personas a las que se los vamos a presentar no entienden qué relación tienen esos insights con el Negocio. ¿Cuál es el reto entonces? Ser capaz de explicar el análisis de
Je m’appelle Franck. Je suis consultant. Depuis 2003, j’accompagne de grands établissements pour renforcer leurs dispositifs de lutte contre le blanchiment et le financement du terrorisme en déployant des progiciels. 17 ans sont passés, ils fonctionnent toujours. Problème : ils sont devenus des monstres ! Je prends conscience de ma
The popular image of data scientists is very much a bit of a geek or nerd. However, that’s not strictly accurate. It may not be – as Harvard Business Review famously suggested – the sexiest job of the 21st century. But it is a long way from the perceived world
Las compañías son hoy más conscientes que nunca de la necesidad de basar su toma de decisiones de negocio en datos para que éstas sean lo más objetivas y fundamentadas posible. Esta tendencia está teniendo un impacto en la demanda de perfiles analíticos, capaces de interpretar los datos y extraer
Decision trees are a fundamental machine learning technique that every data scientist should know. Luckily, the construction and implementation of decision trees in SAS is straightforward and easy to produce. There are simply three sections to review for the development of decision trees: Data Tree development Model evaluation Data The
Remember Subconscious Musings? It was the name of the blog Radhika Kulkarni (now retired Vice President of SAS R&D) started in 2012. She wrote about trends that drove innovation and challenges that expanded the boundaries of what we thought was possible. It eventually evolved into what we now know as
En España se generan más de 22 millones de toneladas de residuos urbanos al año, según datos de la Alianza Residuo Cero, que apunta también a que solo un 30% de ellos acaban siendo reciclados. Para minimizar su impacto en el entorno es fundamental un sistema adecuado de gestión, ya
Skills shortages in data science affect every company and organisation that tries to automate and adopt AI over the next few years.
This post is the second in our Young Data Scientists series, featuring the motivations, work and advice of the next generation of data scientists. Be sure to check back for future posts, or read the whole series by clicking on the image to the right. Kai Woon Goh is
Ever since automated machine learning has entered the scene, people are asking, "Will automated machine learning replace data scientists?"
Through hyperparameter autotuning, you can maximize a model's performance without maximizing effort. While SAS searches the hyperparameter space in the background, you are free to pursue other work.
In February, SAS was recognized as a Leader in the 2020 Gartner Magic Quadrant for Data Science & Machine Learning Platforms report. SAS is the only vendor to be a leader in this report for all seven years of its existence. According to us, the topic of the research is
I caught up with Jaimy van Dijk, one of our youngest female SAS Data Scientists who has proven herself to be a true Rockstar.
Most model assessment metrics, such as Lift, AUC, KS, ASE, require the presence of the target/label to be in the data. This is always the case at the time of model training. But how can I ensure that the developed model can be applied to new data for prediction?
This blog is a part of a series on the Data Science Pilot Action Set. In this blog we review all nine actions in Python. Have you noticed the button bar in the upper right-hand corner of the SAS Visual Data Mining and Machine Learning Programming Guide? This button bar
Data science can be a bit of a lonely job. It’s a shortage specialty, so many data scientists may be the only ones employed by their company. But they still need to learn about what’s new and exciting in the data science world. I caught up with Josefin Rosén about
Meet Stefan Stoyanov. He’s an MSc Business Analytics student with a passion for emerging technologies, ranging from artificial intelligence to augmented and virtual reality.
I asked Jaimy van Dijk if it's true or false if analytics has huge potential in sport.
Crucially, this data not only needs to be standardised but also it needs to be actionable. By that, I mean this behavioural data needs.
Another year, another traditional Christmas song or carol turned into a fun technology-related version! This is the sixth year and my ninth song. I hope you enjoy your 2019 holiday song, based on this famous tune. The Data Science and AI Song Computer vision processing on an open stack The
The dsAutoMl action is all that and a bag of chips! In this blog, we took over all aspects of the data science workflow using just one action.
