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
Tag: machine learning
Computer vision can augment radiologists and make the image interpretation process cheaper, faster and more accurate. The ultimate goal is to achieve a better patient outcome facilitated by the use of computer vision.
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.
Analyzing tweets is challenging because of their succinctness (max 280 characters). However, that task is facilitated by the powerful features of SAS Visual Text Analytics (VTA), which includes embedded machine learning algorithms.
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.
Validating and testing our supervised machine learning models is essential to ensuring that they generalize well. SAS Viya makes it easy to train, validate, and test our machine learning models.
The machine learning autogenerated concept and fact rules in VTA 8.4 facilitate the process of developing LITI rules to extract and find information in text documents. There are many important problems where the use of Text Analytics provides valuable insights such as with Human Trafficking.