#sasprogramming — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #sasprogramming, aggregated by home.social.
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ERROR 180-322: Statement is not valid or it is used out of proper order.
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ERROR 180-322: Statement is not valid or it is used out of proper order.
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ERROR 180-322: Statement is not valid or it is used out of proper order.
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ERROR 180-322: Statement is not valid or it is used out of proper order.
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SAS Programming 1: Essentials - Learn SAS for Data Analysis | CoListy
Start learning SAS programming with essential skills for data access, exploration, preparation, and analysis. Perfect for beginners!
#freeonlinelearning #colisty #courselist #sasprogramming #dataanalysis #sasstudio #sqlinsas #datapreparation #dataexploration #datareporting #sasforbeginners #machinelearning #artificialintelligence #sasenterpriseguide.https://colisty.netlify.app/courses/sas-programming-1-essentials-learn-sas-for-data-analysis/
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Generative AI Using SAS: Explore Machine Learning Techniques | CoListy
Learn the basics of Generative AI with SAS, including SMOTE, GANs, and LLMs to generate synthetic data and improve AI accuracy.
#freeonlinelearning #colisty #courselist #generativeai #machinelearning #datascience #sasviya #gans #smote #largelanguagemodels #bert #ai #syntheticdata #textclassification #rag #sasprogramming.https://colisty.netlify.app/courses/generative-ai-using-sas-explore-machine-learning-techniques/
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Learn SAS Programming for Data Analysis & Reporting | CoListy
Master SAS programming to access, analyze, and report on data. Gain essential skills for data science and machine learning. | CoListy
#freeonlinelearning #colisty #courselist #sasprogramming #dataanalysis #sasstudio #basesas #sasenterpriseguide #datascience #sqlinsas #datareporting #sasprogrammingbasics #learningsas #aiandmachinelearning #datapreparation #sasforbeginners #exportingdatawithsashttps://colisty.netlify.app/courses/sas_-programming-1_-essentials/
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A co-worker using Python is having issues trying to load a dataset. The error is it can't allocate 40+ Gigabytes RAM.
In #SAS programming, this is mostly not an issue because SAS is generally oriented to data sets on disk. It loads a chunk at a time, performs operations, and progressively writing results to disk. Thus, SAS has no hesitation working with data sets much larger than available RAM. A strategy that worked in the 1970s and the 2020s.
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A co-worker using Python is having issues trying to load a dataset. The error is it can't allocate 40+ Gigabytes RAM.
In #SAS programming, this is mostly not an issue because SAS is generally oriented to data sets on disk. It loads a chunk at a time, performs operations, and progressively writing results to disk. Thus, SAS has no hesitation working with data sets much larger than available RAM. A strategy that worked in the 1970s and the 2020s.
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A co-worker using Python is having issues trying to load a dataset. The error is it can't allocate 40+ Gigabytes RAM.
In #SAS programming, this is mostly not an issue because SAS is generally oriented to data sets on disk. It loads a chunk at a time, performs operations, and progressively writing results to disk. Thus, SAS has no hesitation working with data sets much larger than available RAM. A strategy that worked in the 1970s and the 2020s.
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A co-worker using Python is having issues trying to load a dataset. The error is it can't allocate 40+ Gigabytes RAM.
In #SAS programming, this is mostly not an issue because SAS is generally oriented to data sets on disk. It loads a chunk at a time, performs operations, and progressively writing results to disk. Thus, SAS has no hesitation working with data sets much larger than available RAM. A strategy that worked in the 1970s and the 2020s.
-
A co-worker using Python is having issues trying to load a dataset. The error is it can't allocate 40+ Gigabytes RAM.
In #SAS programming, this is mostly not an issue because SAS is generally oriented to data sets on disk. It loads a chunk at a time, performs operations, and progressively writing results to disk. Thus, SAS has no hesitation working with data sets much larger than available RAM. A strategy that worked in the 1970s and the 2020s.