The SAS Data Science Blog
Advanced analytics from SAS data scientists
SAS' Kirk Swilley and Tom Sabo showcase how you can use perform text analysis on minimal structured narrative data to spot patterns of possible human trafficking.
SAS' Sylvia Kabisa shows you how an online media company might use SAS to offer targeted discounts through personalized pricing.
SAS' Marinela Profi and Sophia Rowland elaborate on IDC including SAS among the leading platform providers for Machine Learning Operations.
Anuja Nagpal and Yonglin Zhu of SAS R&D reveal how, MLPA – without any code and within a given timeframe – finds an effective pipeline for a data set after applying data preprocessing, feature engineering and modeling with hyperparameter tuning.
SAS' Bahar Biller expounds on the idea that stochastic simulations are large-data generation programs for highly complex and dynamic stochastic systems.
Building on a previous post on how the seqmc action can be used to mine frequent sequences, SAS' Amod Ankulkar explores an alternative algorithm.
