mikpanko
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ML is known to be good at interpolating between points in the training set, but does much worse at extrapolating. Both can produce innovation when applied to science. For example, a lot of innovation is about…
- AI Guesses Your Accent (start.boldvoice.com)
- Promotion times and rates in data science and analytics (twitter.com)
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My colleague and I tried posting LinkedIn links and while we could see our own posts, we couldn't see each others and we couldn't see them in the incognito mode. Can't find rules about this.
- Causal Discovery for Product Analytics (motifanalytics.com)
- Statisticians Charge Draft Lottery Was Not Random (1970) (nytimes.com)
- Foundation AI Models for Product Analytics (motifanalytics.com)
- That's Weird: Anomaly Detection Using R (pkg.robjhyndman.com)
- Motif Analytics brings sequence analytics to growth teams (techcrunch.com)
- Data Quality Is Misunderstood (twitter.com)
- How can we develop transformative tools for thought? (2019) (numinous.productions)
- From Nand to Tetris (2017) (nand2tetris.org)
- Bringing More Causality to Analytics (motifanalytics.com)