Okay, so today I decided to mess around with something called “Baez Prediction.” Honestly, I’d seen the term floating around and it sounded kinda cool, so I figured, why not?
Getting Started
First things first, I needed to figure out what the heck this thing even was. A quick search revealed it’s related to… well, a bunch of math stuff. Bayesian theory, probability, all that jazz. I’m no math whiz, but I can usually muddle my way through if I have to.
I found some articles and papers online, but honestly, a lot of it went straight over my head. Way too many symbols and equations for my liking. I needed something simpler, something I could actually do.
Finding a Practical Example
Then, it clicked. I should treat this like any other new thing I try. Find an easy implement, get a small win, make a small model for fun. That’s usually how I get the ball rolling.
After a bit more digging, I stumbled upon a simple example of baez prediction about using Bayesian methods to predict if I should bring an umbrella or not for today. That sounded doable! There are just two events to predict, “bring” or “not”.
Building My Little Model
So, I started simple. I created two plain text file, and I start to put my “data” in it.
- raining_*: Put the text “bring” into the file.
- not_raining_*: Put the text “not” into the file.
I opened up my trusty text editor and I wrote these two text file to create a super simple data for my model. The code reads these two files, calculates probabilities, and then makes a “prediction” if I should bring umberlla or not.
Ran the code, and… boom! It works!
My “Aha!” Moment
The code works, I am pretty sure that I understand how it works, at a basic *’s about updating probabilities based on new evidence.
But, the most important thing is to understand that I can replace the text with any category word, like “buy” and “not” for stock price prediction.
What’s Next?
Honestly, this was just a tiny first step. There’s so much more to explore with Bayesian methods and prediction in general. But, for today, I’m happy. I took something that sounded intimidating, broke it down, and made something that (sort of) works. And that’s a win in my book.
I might try to apply this to something a bit more interesting than my umbrella – maybe predicting my team’s project schedule, or something like that. We’ll see!
