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US Economic Outlook 2025
With the 2024 election in the rear view mirror, we have a better picture of what policy for the next few years is going to look like. As such, we have a better idea on what to expect from the US economy over the next few years. That has largely colored my analysis this year.…
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Bayesian Time Varying Coefficients in PYMC3
Okay so today I want to talk about something really cool that you can do with time-series / panel data. That is, you can allow the coefficients in the model change over time. It is a really neat idea, but it creates a challenge for writing down the model in most of the traditional regression…
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Using LSTM networks in Keras to Predict Baby Name Popularity
So its time for a fun little announcement, my wife and I are having a baby. And we’re so excited! Having a baby presents a novel problem for every parent every time. And that is: “We’re going to have a little human being running around, and that human is going to need a name.” It…
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SKLearn in Production
Alright, I’m kind of in a time crunch this week because I took off for Labor Day weekend. As such I just want to write a quick little post so that you guys don’t think I’m slacking in my posting something every week on Wednesday. So this is basically a quick tutorial on how to…
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Learning XOR with Only Linear Regression (Yeah it’s Possible)
Alright, so that title isn’t very clickbaity unless you are a real data nerd. Linear models do terrible at learning XOR. Simply because XOR is highly non-linear. It requires a non-linear model to learn it. And my model is non-linear too. But the only model that I use is a linear regression, straight up OLS.…
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3 Reasons to Fall in Love With Bayesian Statistics
So for the past month or so, I have been writing a lot of posts about Bayesian Statistics.You might be wondering why I’ve spent so much time in the area. You might even suspect that you know the answer, but let me share 3 reasons why I enjoyed working with Bayesian Statistics this last month…
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5 Resources to Get you Started in Data Science
Data science is a huge and ever expanding field. It deals heavily with math, computers, statistics, and all sorts of other disciplines. Jumping into data science often feels overwhelming, because frankly, it is. I often hear questions similar to this one from my buddy from grad school, Nii Amon Neequaye, PhD: “… do u have…
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Monte Carlo Integration in Python
My last post was pretty intense, so I thought that I would drop back down to something a little bit simpler for this post, before I go off and start in on the March Madness stuff again. It turns out that writing that last post really kicked my butt, so I’m taking a bit of…
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Predicting March Madness Winners with Bayesian Statistics in PYMC3!
So in the last two blog posts, I talked about how to do some bayesian inference in the realm of some linear models. And that is all well and good, but we can have even more fun in a bayesian framework. That’s because we are just sampling things from probability distributions. In this post I…
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Bayesian Logistic Regression in Python using PYMC3
In my last post I talked about bayesian linear regression. A fairly straightforward extension of bayesian linear regression is bayesian logistic regression. Actually, it is incredibly simple to do bayesian logistic regression. If you were following the last post that I wrote, the only changes you need to make is changing your prior on y…
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Bayesian Poisson A/B Testing in PYMC3 on Python
This post is a direct response to the request made by @Zecca_Lehn on twitter (Yes I will write tutorials on your suggestions). What he wanted to know was how to do a Bayesian Poisson A/B tests. So for those of you that don’t know what that is let’s review the poisson distribution first. The poisson…