Using State Space Models for the Stability Monitoring of Streaming Data
SAS' Rajesh Selukar introduces you to a new scoring feature.
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How SAS developed a digital twin of a supply chain
SAS' Bahar Biller, an operations researcher, details how to develop a supply chain digital twin.
Who else wants to know the mystery behind GANs?
Generative adversarial networks (GANs) are one of the newer machine learning algorithms that data scientists are tapping into. When I first heard it, I wondered how can networks be adversarial? I envisioned networks with swords drawn going at it. Close… but I can assure you that no networks were harmed in the making of this article.
Art or science? Choosing the right regression model
SAS' Udo Sglavo and Jan Chvosta discuss the power of a regression framework and choosing the correct regression model.
Which regression technique is appropriate for my data?
SAS' Udo Sglavo interviews colleague Jan Chvosta, director of Scientific Computing at SAS, on regression analysis and how it works.
SAS Leads Market 28 Years in a Row, IDC Advanced & Predictive Analytics Software
IDC measures advanced & predictive analytics in its annual Worldwide Business Intelligence and Analytics Software Market Shares* report – and has consistently ranked SAS as the #1 market leader for over two decades!
Generating word embeddings
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.
Causal inference and policy evaluation with deep neural networks
SAS' Xilong Chen introduces the new DEEPCAUSAL procedure in SAS Econometrics for causal inference and policy evaluation and much more.
Analyzing movement and tracking data using SAS Visual Analytics
Technological advancements in connectivity and global positioning systems (GPS) have led to increased data tracking and related business use cases to analyze such movements. Whether analyzing a vehicle, an animal or a population's movements - each use case requires analyzing underlying spatial information. Global challenges such as virus outbreaks, deforestation
Build and deploy a machine learning pipeline using SAS and Python
This post, written by Radhikha Myeni and Jagruti Kanjia, will demonstrate how easy it is to build and deploy a machine learning pipeline by using SAS and Python. The Model Studio platform provides a quick and collaborative way to build complex pipelines by dragging and dropping nodes from a web-based