#Hydrology #PredictiveModeling #AI
Could AI help predict catastrophic floods? This Virginia Tech professor thinks so
#Predictivemodeling
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#AIsimulations #Industrialprocessoptimization #ManufacturingAI #Datadrivendecisionmaking #Predictivemodeling
We in the US are living in a eugenic modernity, by the way, when the putative head of "Health and Human Services" is making the kinds of statements he makes about autistic people. This is not just an anti-vaccination meme; it's an attempt to subordinate an entire class of people, suggesting they are subhuman for being who they are. This is a eugenic move. One has to wonder whether the "human services" people in HHS imagine themselves providing has to do with "improving the human stock" of the nation, the services not being provided to humans but instead having humans as an output.
Rather than get mired in the thought-terminating arguments around political parties or political factions, though, I think we'd do well to reflect on what sorts of other ways of thinking feed into this one: the measured life; standardized testing; the internet of things (sensors); tracking apps of various kinds; electronic health records; data science as a profession and Big Data generally; predictive modeling; generative AI and other optimization-oriented or productivity-promising technology. All of these function to render life as an object of knowledge in one way or another. All of them trace their origins through eugenics and the patterns of thought that led to it, and all of them threaten to enable and enhance further eugenic thinking. This is not to say these things are always all bad; this is meant to be a reflection on what exactly they're for.
Why read the number of steps your FitBit told you you took today, unless there were some sense in which you want your future self to be better than your present self? It's not an accident that this is called "physical fitness", "fitness" being the Darwinian concept describing which organisms should survive. Why subject children to standardized testing unless there were some belief it made them better students? To what end tends to be left out. Why adopt a technology meant to improve productivity, unless you're of the belief that improvement (optimization) were even possible?
Generally speaking, if one is able to bring oneself to believe that a human being is made better by a data-informed technical intervention, isn't one playing the same game as these anti-autism anti-vaxxers, just with different terminology? If your answer to this provocation is that your data is better than theirs or that you're more aligned with reality than they are--some variation of "the science is on our side"--you've ceded the territory: this is more of the same optimization logic that brought us to this point to begin with. I think we have no choice but to do better than this.
That's my reflection anyway.
#USPol #autism #vaccination #vaccines #antivax #eugenics #BigData #AI #PredictiveModeling #DataScience #science
Rather than get mired in the thought-terminating arguments around political parties or political factions, though, I think we'd do well to reflect on what sorts of other ways of thinking feed into this one: the measured life; standardized testing; the internet of things (sensors); tracking apps of various kinds; electronic health records; data science as a profession and Big Data generally; predictive modeling; generative AI and other optimization-oriented or productivity-promising technology. All of these function to render life as an object of knowledge in one way or another. All of them trace their origins through eugenics and the patterns of thought that led to it, and all of them threaten to enable and enhance further eugenic thinking. This is not to say these things are always all bad; this is meant to be a reflection on what exactly they're for.
Why read the number of steps your FitBit told you you took today, unless there were some sense in which you want your future self to be better than your present self? It's not an accident that this is called "physical fitness", "fitness" being the Darwinian concept describing which organisms should survive. Why subject children to standardized testing unless there were some belief it made them better students? To what end tends to be left out. Why adopt a technology meant to improve productivity, unless you're of the belief that improvement (optimization) were even possible?
Generally speaking, if one is able to bring oneself to believe that a human being is made better by a data-informed technical intervention, isn't one playing the same game as these anti-autism anti-vaxxers, just with different terminology? If your answer to this provocation is that your data is better than theirs or that you're more aligned with reality than they are--some variation of "the science is on our side"--you've ceded the territory: this is more of the same optimization logic that brought us to this point to begin with. I think we have no choice but to do better than this.
That's my reflection anyway.
#USPol #autism #vaccination #vaccines #antivax #eugenics #BigData #AI #PredictiveModeling #DataScience #science
How do you handle imbalance in your ML workflows?
Drop your thoughts in the comments! Let's start a conversation about responsible and effective machine learning practices. 💬👇
https://onlinelibrary.wiley.com/doi/full/10.1002/sim.10320
#MachineLearning #DataScience #AI #SMOTE #ImbalancedData #MLResearch #PredictiveModeling
True story time. ~7 years ago, onsite team meeting
New hire said when starting job, they thought "model" in job description meant we take photos, wondered where the girls were. Initially sounded like joke, but as they kept going, I realized they were serious. Next few years confirmed laziness, lack of curiosity.
How do you see "model" in #DataAnalytics job & not research it enough to know it means "predictive model" before interview?
Let’s unlock the future of predictive modeling together! 🔑 #DataScience #MachineLearning #PredictiveModeling #ConformalPrediction
Let’s unlock the future of predictive modeling together! 🔑 #DataScience #MachineLearning #PredictiveModeling #ConformalPrediction
Let’s unlock the future of predictive modeling together! 🔑 #DataScience #MachineLearning #PredictiveModeling #ConformalPrediction
Let’s unlock the future of predictive modeling together! 🔑 #DataScience #MachineLearning #PredictiveModeling #ConformalPrediction
Let’s unlock the future of predictive modeling together! 🔑 hashtag#DataScience #MachineLearning
#PredictiveModeling
#ConformalPrediction
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Learn essential statistical techniques like ANOVA, regression, and logistic regression using SAS software. Perfect for beginners!
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Prepare for Predictive Modeling Using SAS Enterprise Miner® | CoListy
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Master SAS/STAT for Complex Statistical Analysis | CoListy
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Master Data Science with SAS and Python for Customer Churn | CoListy
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Master Advanced Analytics with SAS Viya | CoListy
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Intro to Statistical Analysis with SAS/STAT Software | CoListy
Learn t-tests, ANOVA, regression, and predictive modeling with SAS/STAT. Master essential statistical techniques for data analysis. | CoListy
#freeonlinelearning #colisty #courselist #sas/stat #statisticalanalysis #anova #regression #logisticregression #predictivemodeling #sasprogramming #procglmselect #datavisualization #categoricaldataanalysis #hypothesistesting #proclogistic
Let’s unlock the future of predictive modeling together! 🔑 #DataScience #MachineLearning #PredictiveModeling #ConformalPrediction
#TitanicDatase with detailed visualizations and insights. Learn about #DataPreprocessing, #SurvivalRates, passenger demographics, and #PredictiveModeling techniques. This comprehensive guide covers all aspects for data science enthusiasts.
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