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.
Stuttgarter Zukunftssymposium - was werden Maschinen in Zukunft wirklich sein - Angst also vorbei?
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.
„Die Kommunikation in Rhein Main ist wirklich schlecht. Weder die Startups reden untereinander noch die Firmen.“
Are you looking for a Data Science easy button? The dataSciencePilot action set comes pretty close.
Data-driven businesses use technology as an insight platform to empower nontechnical users.
Are you looking for a Data Science easy button? The Data Science Pilot Action Set comes pretty close.
Nowadays, geeks are increasingly cool, and we’re all proud to let our inner geek out in public. This wasn't always so ...
There is a lot of excitement about AI, but somehow the reality is not really living up to the hype. At the moment, we don’t see enough real results or use cases emerging, even though everyone agrees that there is huge potential. I polled some of our experts to find
O testemunho de Maria do Carmo Castro Correia, que usufruiu do Software SAS e pôde comprovar, por experiência própria, a sua utilidade assim como o apoio incondicional dado pela equipa de pessoas que fazem parte do SAS. A relação do SAS com o mundo académico é algo que vem
Without the right data, any analytics initiative is just an illusion. For machine and deep learning efforts, new sources of data are always in demand. In a few of our Innovation at Scale study interviews, respondents pointed to the rising need for data hunters. I asked our resident guru on
Technological advancements are changing every industry – and the health care industry is no exception. The value of AI has never been greater than when it’s used to improve patients’ conditions and save lives. For example, Cancer Center Amsterdam joined forces with SAS to improve patient care outcomes with AI.
Move over video games and sports. Make room for escape rooms. This burgeoning form of entertainment found its roots in the video gaming movement. Escape rooms tap into a player's drive to reach the next level, solve a puzzle and win. Escape rooms present a physical game that traps you
Data Scientists verbringen eine Menge Zeit mit Daten. Dabei gilt immer – von der Anwendung von Machine-Learning-Modellen bis hin zum Trainieren von KI-Modellen: Mit der Datenqualität stehen und fallen die Ergebnisse. Analytics und Data Science stellen jedoch nicht nur Ansprüche an Datenqualität. Sie können auch dazu beitragen, diese zu verbessern.
Der Sales Manager kann sich bezüglich des zu erwartenden Jahresergebnisses doch nicht so in Sicherheit wiegen, wie er dachte. Hans Huber aus unserem Callcenter hat eine höhere Wahrscheinlichkeit zu kündigen als Petra Hafner aus dem Controlling. Die Transaktionsverläufe der Kunden 42911, 85022 und 91294 passen ja gar nicht zu deren
UK government departments and the wider public sector are under huge pressure to improve service delivery and efficiency. We also know that investments in data analytics and data science play a key role in transforming services to help citizens. So what are the key challenges preventing more widespread adoption of
„Die wichtigsten Dinge schreibt man am besten gleich in die Einleitung! Eventuell lesen einige ja gar nicht bis zum Hauptteil weiter“. Einen ähnlichen Gedanken hatte ich bei meinem aktuellen Buch Applying Data Science – Business Case Studies Using SAS auch. Da sind bereits in der Einleitung die Mehrwerte aufgezählt, die
The Economist magazine takes pride in its ability to provoke deeper thinking. One of its campaigns was to ask people to taste weird-looking foods, such as smoothies made from “ugly” produce that had been rejected by supermarkets. The idea was to stimulate participants to reassess what was important to them.
Diese Frage bekomme ich von Nicht-Data-Scientists immer häufiger gestellt. Und es ranken sich viele Meinungen und Mythen um diese Expertengruppe. Genau aus diesem Grund habe ich mich mit Simon Greiner, einem angehenden Data Scientist und erfahrenen IT-Berater, unterhalten. Ein Mythos über Data Scientists: sie lesen keine Bücher mehr. Stimmt nicht!
