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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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Christmas Give Away
Guess what? I’m giving away an hour of data science coaching and a $50 gift card for Christmas this year. That’s right, ho ho ho! Merry Christmas! On every page on the website you will see a nice little opt in form. If you enter your email address, you get one entry, and for every…
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Why I am Offering Coaching Sessions
Why Coaching Usually I post a tutorial about a data science topic, sometimes I write a post about something a little bit more meta about data science like how to get started as a new comer, on occasion I’ll recommend some books that I’ve read. Today is something different. I want to introduce you to…
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Logistic Regression in R
Logistic regression was like magic the first time that I saw it. I grasped the utility almost immediately, but then I was shown how to hang economic theory on top of logistic regression and my face melted! Then I learned about the assumptions in logistic regression that no one seems to talk about like the…
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Bayesian Auto-Regressive Time Series Analysis in PYMC3
I have written a lot of blog posts on using PYMC3 to do bayesian analysis. And I have a few where I have even dealt with Time-Series datasets. To name a one, I have done one on time varying coefficients. In this post, I want to explore a really simple model, but it is one…
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3 Books that I Recommend to Learn Machine Learning
Today, I’m going to take a simple approach to the blog post. I’m working on some other things so, I need to scale this one back. So I’m going to give you 3 books that I recommend to learn general machine learning. I think that these books have been influential to the way that I…
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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…