All proceeds to the MSU economics PhD program.
econ.msu.edu/academics/es...
All proceeds to the MSU economics PhD program.
econ.msu.edu/academics/es...
youtu.be/NS7SjHDSdmA?...
youtu.be/NS7SjHDSdmA?...
🧵
🧵
dl.acm.org/doi/pdf/10.1...
dl.acm.org/doi/pdf/10.1...
But what if it isn't?
I built an #rstats GAM for SaaS revenue prediction that captures:
→ Nonlinear adoption curves
→ Tier-specific behaviors
→ Feature value with uncertainty
ecogambler.netlify.app/blog/clv-pre...
GPs are super interesting, but it’s not easy to wrap your head around them at first 🤔
This is a medium level (more intuition than math) introduction to GPs for time series.
getrecast.com/gaussian-pro...
GPs are super interesting, but it’s not easy to wrap your head around them at first 🤔
This is a medium level (more intuition than math) introduction to GPs for time series.
getrecast.com/gaussian-pro...
The file drawer problem but for guilty verdicts
The file drawer problem but for guilty verdicts
At #PyDataBerlin, @nathanielforde.bsky.social shows how PyMC Marketing’s new Consumer Choice module uses Bayesian models for realistic substitution.
🗓️ Sept 1, 4:20 PM | 📍 Room B05-B06
#BayesianStats #PyMC
At #PyDataBerlin, @nathanielforde.bsky.social shows how PyMC Marketing’s new Consumer Choice module uses Bayesian models for realistic substitution.
🗓️ Sept 1, 4:20 PM | 📍 Room B05-B06
#BayesianStats #PyMC
I've released my new open source book, "Powered by Linear Algebra: the role of matrices and vector space in data science," at matloff.github.io/WackyLinearA....
Turns the classic LA course on its head! Still proves the theorems, but with a deep emphasis on applications.
I've released my new open source book, "Powered by Linear Algebra: the role of matrices and vector space in data science," at matloff.github.io/WackyLinearA....
Turns the classic LA course on its head! Still proves the theorems, but with a deep emphasis on applications.
en.wikipedia.org/wiki/Don%27t...
en.wikipedia.org/wiki/Don%27t...
nathanielf.github.io/posts/post-w...
It’s not one score. It’s a bundle: how we feel ❤️, how we work 💼, how we think 🧠.
Here’s what happened when we tried to compress that complexity… 🧵
nathanielf.github.io/posts/post-w...
It’s not one score. It’s a bundle: how we feel ❤️, how we work 💼, how we think 🧠.
Here’s what happened when we tried to compress that complexity… 🧵
berlin.pydata.org/conferences/...
berlin.pydata.org/conferences/...
Use a formula API to model product choices & customer preferences — all in a Bayesian workflow 🧠📊
Docs:
🔗 l1nq.com/KRb64
🔗 encr.pw/oa49I
@pymc.io #discrete-choice #bayesian #stats #causal-inference
Use a formula API to model product choices & customer preferences — all in a Bayesian workflow 🧠📊
Docs:
🔗 l1nq.com/KRb64
🔗 encr.pw/oa49I
@pymc.io #discrete-choice #bayesian #stats #causal-inference
I arrived at the conclusion that (1) there's a lot of interesting stuff about interactions and (2) the figure I was looking for does not exist.
So, I made it myself! Here's a simple illustration of how to control for confounding in interactions:>
My talk on Causal Inference with @pymc-labs.bsky.social CausalPy package is here. Can we trust individual IV designs. What's the role of CI in industry?
Recording: youtu.be/-C4p4b2cUp8?...
Deck: nathanielf.github.io/talks/pycon_...
My talk on Causal Inference with @pymc-labs.bsky.social CausalPy package is here. Can we trust individual IV designs. What's the role of CI in industry?
Recording: youtu.be/-C4p4b2cUp8?...
Deck: nathanielf.github.io/talks/pycon_...
www.meetup.com/pythonirelan...
www.meetup.com/pythonirelan...