Matt Mills

Data Scientist at Intuit/Mailchimp. I like to share random musings on R, Stats, and College Football

[Matt Mills @statmills]

I've uploaded some CFB Data for open source use https://t.co/YpY8nkZ8xH 10 years of

Team recruit rankings
Draft Picks
Schedule and Results

[Matt Mills @statmills]

Very cool to find a well written statistics blog post like we used to see all the time on this app: @bruno_nicenboim giving a walkthrough of Ordinal Models with {brms} https://t.co/s96IO8dSBL #rstats

[Matt Mills @statmills]

@stevehou How so? This is just a scarce physical good with very high status signaling having a ton of demand. NYC isn’t even an AI town with tons of VC money flowing in to that industry like SF.

[Matt Mills @statmills]

@HowEPhil This is one of the arguments I wish people made more. More people means more tax payers and more customers for small businesses. Spreading our fixed costs over more people would actually lower the cost of city services per person

[Matt Mills @statmills]

@atlurbanist As multiple other commenters have pointed out this article is total BS. If you get upset when someone shares out of context, misleading, BS about how transit makes the city worse then why don’t you put the same effort in to educating yourself on this topic?

[Matt Mills @statmills]

CFB/NFL Legend Ndamukong Suh going full YIMBY belongs in @TheZvi ‘s next housing roundup.

[Ndamukong Suh @NdamukongSuh]

Everyone wants more housing. Until it’s time to actually build it.

The shortage isn’t supply. It’s the system that decides whether supply gets built.

[Matt Mills @statmills]

@analyticsaurabh The shortest players are not the best these days; Jokic, LeBron, Giannis, Wemby, KD, etc... Take your pick, but you are starting with someone 6'9" or higher. And really only Steph Curry has been in contention for a short player being the best recently.

[Matt Mills @statmills]

@bburkeESPN Thanks for being open and sharing these detailed of results. Did y'all explore monotonic constraints on the features? I'm not sure if some of these PDP make 100% sense; should it ever be better to bench less, all else equal?

[Matt Mills @statmills]

You can extend Gradient Boosting to fit many more models than just target predictions. My blog post from earlier this week walks through how you can fit the coefficients of smoothing splines with Gradient Boosting https://t.co/LhV0KVPJlA

[Matt Mills @statmills]

I have a new blog post out today that I'm really excited about. I walk through how you can use Gradient Boosting to fit entire vectors of parameters for each observation, not just a single prediction.

[Matt Mills @statmills]

@DuaneJRich I have had GRFs saved to follow up on for a while and seeing this tweet inspired me to lean in and led to a somewhat related post. I know AI can explain things better than any textbook now, but I still enjoy rolling up my sleeves and digging in myself. https://t.co/5GHawC8QRA

[Matt Mills @statmills]

I have a new blog post out today that I'm really excited about. I walk through how you can use Gradient Boosting to fit entire vectors of parameters for each observation, not just a single prediction.

[Matt Mills @statmills]

I hope people find this walkthrough useful! https://t.co/LhV0KVPJlA

[Matt Mills @statmills]

I have a new blog post out today that I'm really excited about. I walk through how you can use Gradient Boosting to fit entire vectors of parameters for each observation, not just a single prediction.

[Matt Mills @statmills]

The result is smooth curves that can learn high dimensional interaction effects that you can fit at scale!

[Matt Mills @statmills]

@peterwildeford *right

[Matt Mills @statmills]

@peterwildeford I actually just recently wrote about this; Data Science requires a lot of foundational steps to be write in a way that is different than other software dev https://t.co/lcNo23mX3D

[Matt Mills @statmills]

This is a very *rough* framework I know, but it was helpful for me to think about it in this way to figure out what tools and processes I needed to build to improve the generated code I use for data analysis. I hope its helpful to others as well. https://t.co/lcNo23mX3D

[Matt Mills @statmills]

I've got a new blog post out about how to do proper Data Science in the age of LLMs. My thesis is that DS is a multiplicative process which separates it from more traditional software dev; if one assumption is off then the result is wrong in a way it isn't with a UI (1/3)

[Matt Mills @statmills]

My biggest struggle is that AI can produce code that runs but may violate an assumption about the data; observations get dropped, duplicated, or mis-aligned without you knowing (2/3)