Accelerating delivery with CI/CD – Navigating the journey
SAS' Mary Carter details challenges and benefits of accelerating the delivery of SAS software.
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Curious about ChatGPT: Exploring the origins of generative AI and natural language processing
How did we get to a place where a conversational chatbot can quickly create a personalized letter? Join us as we explore some of the key innovations over the past 50 years that help inform us about how to respond and what the future might hold.
Innovative contributions to NeurIPS 2022
NeurIPS 2022 allowed researchers and practitioners to share progress and brainstorm new ideas for advancing machine learning and its related fields.
Improving the detection of level shifts using the median filter
Time series data is widely used in various fields, such as finance, economics, and engineering. One of the key challenges when working with time series data is detecting level shifts. A level shift occurs when the time series’ mean and/or variance changes abruptly. These shifts can significantly impact the analysis and forecasting of the time series and must be detected and handled properly.
Leveraging text analytics and AI to assess police narrative events indicating human trafficking
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.
Using PROC DEEPPRICE to personalize prices and optimize revenue
SAS' Sylvia Kabisa shows you how an online media company might use SAS to offer targeted discounts through personalized pricing.
The SAS MLOps solution outperforms vendors such as DataRobot, Databricks, Dataiku, Domino Data Lab, Iguazio, according to IDC MarketScape 2022
SAS' Marinela Profi and Sophia Rowland elaborate on IDC including SAS among the leading platform providers for Machine Learning Operations.
Automate your machine learning pipeline in SAS Viya
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.
Accelerating what-if analysis with machine learning
SAS' Bahar Biller expounds on the idea that stochastic simulations are large-data generation programs for highly complex and dynamic stochastic systems.
Using the cspade action to find frequent gene sequences
Building on a previous post on how the seqmc action can be used to mine frequent sequences, SAS' Amod Ankulkar explores an alternative algorithm.