Sophia Rowland is a Senior Product Manager focusing on ModelOps and MLOps at SAS. Previously, Sophia was a Systems Engineer on a team that focuses on Data Science and ModelOps applications for the Financial Services industry. Sophia is an active speaker and author in the field of ModelOps. She has spoken at All Things Open and SAS Explore and has written dozens of blogs and articles for Open Data Science, SAS Communities, and the SAS Data Science Blog. Sophia is an alumnus of both UNC-Chapel Hill and Duke. At UNC-Chapel Hill, Sophia double majored in Computer Science and Psychology. At Duke, Sophia attended the Fuqua School of Business and completed a Master of Science in Quantitative Management: Business Analytics. After work, Sophia can be found reading, hiking, and baking.
SAS Model Manager and the sasctl packages aim to create a seamless ModelOps and MLOps process for Python and R models. Python and R models are not second-class citizens within SAS Model Manager. SAS, Python, and R models can be easily managed using our no-code/low-code interface. This is an interface that can be extended to support a variety of use cases.
You can start learning about ModelOps and SAS Model Manager now. Compare the various educational resources provided by SAS according to your learning preference.
Word embeddings are the learned representations of words within a set of documents. Each word or term is represented as a real-valued vector within a vector space. Terms or words that reside closer to each other within that vector space are expected to share similar meanings. Thus, embeddings try to capture the meaning of each word or term through its relationships with the other words in the corpus.
SAS System Engineer Sophia Rowland reveals how to embed decision flows into webpages and applications using the Microsoft Power Platform for a better customer experience.
SAS System Engineer Sophia Rowland reveals how to embed decision flows into webpages and applications using APIs for a better customer experience.
SAS and Microsoft certifications can help with your professional and career development. And now, you can even take certification exams from the comfort of your own home.
With the release of SAS Viya 2020.1.4, text categories and concept models can now be deployed into production with just a few clicks and used to score data in-batch and via API! You can also now use these models in decision flows.
The Text Investigation Framework is a flexible solution for addressing text challenges across several domains. It was designed to create a process for turning unstructured text data into a decisioning system.
We will use prescriptive analytics and optimization to select a stock portfolio that maximizes returns while taking risk tolerance into account.
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.
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
This blog is a part of a series on the Data Science Pilot Action Set. In this blog, we discuss updates to Visual Data Mining and Machine Learning with the release of Viya 3.5. In the middle of my blog series, SAS released Viya 3.5. Included in Viya 3.5 was the
This blog focuses on using SASPy for modeling and machine learning.
SAS Viya is a cloud-enabled, in-memory analytics engine which allows for rapid analytics insights. Viya utilizes the SAS Cloud Analytics Services (CAS) to perform various actions and tasks. Best of all, CAS is accessible from various interfaces including R. In this blog, I will go through a few blocks one of my notebooks, which moves through an analytics workflow using R and SAS.
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.
Are you looking for a Data Science easy button? The dataSciencePilot action set comes pretty close.
Are you looking for a Data Science easy button? The Data Science Pilot Action Set comes pretty close.
