Finding Natural Groups in Transaction Data
All the attention right now is on large language models. But there's a whole category of machine learning that's been quietly useful for years and doesn't require a GPU or a billion parameters. Clustering is one of those techniques. The idea is simple. Given a pile of client data, can an algorithm find natural groups without being told what to look for? I wanted to try it.
Using Matplotlib to See What the Numbers Hide
Exploring transaction data with pandas gave me a baseline. Counting things, grouping things, building a sense of what normal looks like. That was useful, but it left me staring at tables of numbers. What I wanted was to see the shape of what's happening over time.
A Million Bank Transactions from a Public Dataset
I wanted to try the same data tools on transaction-level records. Mortgage lending data is useful, but the day-to-day activity of a bank lives in its transactions. Deposits, withdrawals, transfers, loan payments. Every client interaction with their account generates a record.
Putting the Tools to Work on Real Data
With Jupyter, pandas, and matplotlib set up, let's put those tools to work on real data.
A Personal Workbench for Data Exploration
Any real work with data starts with actually looking at it. Before reaching for a heavyweight analytics platform, the fastest way to get your hands on a dataset is a notebook running on your own machine. That personal workbench is where I do most of my exploring, and Jupyter is what powers it.
How Python and Turtle Made Programming Click
As a software developer and dad to two curious boys, I live in one world of code and another of LEGOs. Watching my kids snap together simple blocks to build increasingly complex creations, I can't help but see the similarity to how we build software from just a few basic "blocks" of code.
The Final Project
In the previous unit, we covered game loops, state management, and collision detection. Now let's put it all together and build Snake.
Building Interactive Games with Turtle
In the previous unit, we covered project management with Poetry. Now we're shifting back to Turtle graphics to explore game development concepts that we'll use in the final unit to build Snake.
Modern Python Dependency Management
In the previous unit, we used pip and requirements.txt to manage dependencies. Poetry takes this further with a more complete project management workflow.
Isolating Your Project's Dependencies
In the previous unit, we learned to share code through GitHub. Now let's talk about managing the packages your code depends on.
