https://aeturrell.github.io/markov-wanderer/posts/data-science-maturity/data-science-maturity.html Data science maturity and the cloudArthur TurrellMarch 1, 2023 “So, if you’re looking at your own organisation’s data science offering, what are the key things you should be able
What I Read: Predict Distributions
https://towardsdatascience.com/a-new-way-to-predict-probability-distributions-e7258349f464?gi=3201d118e909 A New Way to Predict Probability DistributionsExploring multi-quantile regression with CatboostHarrison HoffmanFeb 14 “Until recently, the main disadvantage of quantile regression was that one model had to be trained
What I Read: Geometric Deep Learning
https://thegradient.pub/towards-geometric-deep-learning/ Towards Geometric Deep LearningMichael Bronstein18.Feb.2023 “Geometric Deep Learning is an umbrella term for approaches considering a broad class of ML problems from the perspectives of symmetry and invariance.”
What I Read: Teach Computers Math
https://www.quantamagazine.org/to-teach-computers-math-researchers-merge-ai-approaches-20230215/ To Teach Computers Math, Researchers Merge AI ApproachesKevin HartnettFebruary 15, 2023 “Large language models still struggle with basic reasoning tasks. Two new papers that apply machine learning to math
What I Learn: SQL, Malloy
https://carlineng.com/?postid=sql-renaissance#blog SQL, Malloy, and the Art of the RenaissanceCarlin Eng02.05.2023 “By allowing sub-tables within resultsets, Malloy results are able to faithfully represent the true dimensionality of the underlying data.”