Michael Clark @statsdatasci
Statistical Philosopher, Brute Empiricist m-clark.github.io Ann Arbor Joined September 2016-
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Michael Clark retweeted
From classic techniques to cutting-edge machine learning, data science models help uncover patterns and power smarter predictions. Check out our latest blog post for key insights from Michael Clark's book "Models Demystified": bit.ly/4hIwnic
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Michael Clark retweeted
I hope @statsdatasci doesn't mind me announcing that this book will be published by Chapman and Hall/CRC likely in 2024.
I hope @statsdatasci doesn't mind me announcing that this book will be published by Chapman and Hall/CRC likely in 2024.
I've been putting together a book on modeling that I hope will appeal to a wide range of audiences, with examples in Python/R. You can check out the in-progress work at: m-clark.github.io/book-of-models/. Hope you find it useful, and feedback is appreciated as we continue to work on it!
Michael Clark retweeted
Here are some helpful #guidelines for working with tabular #data buff.ly/3ZjT3fI #deeplearning #tabulardata
The @stronganalytics blog has really come alive this year and is now providing near weekly posts on topics in data science, #AI, and related. I also contributed a few weeks ago! 😄 #DataScience strong.io/blog/ strong.io/blog/deep-lear…
After seeing some frustrating pks at the world cup, I used some data found on kaggle, #brms and #tidybayes to get some posterior predictive distributions for probability of goal by location/zone kicked. Fun data to play with! #WorldCup2022
Updated my {mixedup} 📦. If you switch among multiple mixed model packages but would like a similar set of functions/tidy results whichever one you're using, then this may be of use to you. github.com/m-clark/mixedu… m-clark.github.io/mixedup/ #rstats
New post demonstrating time series modeling from arima to deep learning with CTA ridership data. Complements @CodyDirks recent post at the @stronganalytics blog ( strong.io/blog/forecasti…). m-clark.github.io/posts/2021-05-… #rstats #gam #pytorch
New post on some programming explorations with an eye toward speed and memory efficiency. Hopefully can help others when doing similar operations. m-clark.github.io/posts/2022-07-… #rstats
Updated my doc on Generalized Additive Models! Cleaned up code, plots, updated tools/packages, added small section on Bayesian GAM, etc. m-clark.github.io/generalized-ad… #rstats #GAM
New post summarizing some additional recent articles of applications of DL models for tabular data. Includes a summary of all findings reviewed in this and a previous post. m-clark.github.io/posts/2022-04-…
Another document update, this time to my Bayesian introduction with Stan as the backdrop. Clarified some text and (very old) code, along with a little bit of content update here and there. Enjoy! m-clark.github.io/bayesian-basic… #rstats @mcmc_stan
Doing some minor updates to my mixed model doc, esp. for clarity. Suggestions welcome, so feel free to post an issue on GitHub! github.com/m-clark/mixed-… m-clark.github.io/mixed-models-w…
Neglected to note a couple blog posts last year (better late than never?): Summary of articles exploring the effectiveness of deep learning vs. other methods (esp. boosting) for tabular data: m-clark.github.io/posts/2021-07-… Demo of the double descent phenomenon: m-clark.github.io/posts/2021-10-…
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