AI Project: Fine-Tuning a Hugging Face Model (Part 1: The Data)
You’ve used Hugging Face pipelines to run pre-trained models. If you want to get the most from these models, learning about Hugging Face Fine-Tuning is…
Reshaping Data in Polars: The melt() Method (Unpivoting)
Your data is often in a “wide” format, like a spreadsheet, but analysis tools (like plotting libraries) prefer “long” format. One useful function for this…
AI Project: Using Hugging Face Agents (Your Personal AI Assistant)
This is the cutting-edge of AI, far beyond a simple pipeline. An Agent is an LLM (like ChatGPT) that has been given tools and can…
AI Project: Zero-Shot Classification with Hugging Face
This is one of the most powerful and “magical” tasks in modern AI. In particular, Hugging Face Zero-Shot is a technique that demonstrates impressive versatility…
Conditional Logic in Polars: The when/then API (SQL Case When)
One of the most common data tasks is creating a new column based on a condition. In this tutorial, we’ll focus on using Polars when…
AI Project: Object Detection with Hugging Face (DETR)
We’ve taught our AI to classify an image (e.g., “This is a cat”). Now let’s teach it to find the cat. Object Detection is a…
Working with Dates in Polars: The .dt Namespace (2026 Guide)
Just loading dates isn’t enough. For real analysis, you need to “engineer features” from them, like “What day of the week do most sales happen?”…
Handling Nested Data in Polars: explode() and unnest()
Real-world data from APIs often comes as nested JSON. Pandas struggles with this, but Polars has two powerful expressions built for it: explode and unnest….
AI Project: How to Deploy a Hugging Face Model as a REST API (with Flask)
You’ve built amazing AI models with Hugging Face, but they’re stuck in your script. Want to know how to deploy Hugging Face API so other…
Cleaning Text in Polars: The .str Expression Namespace
Text data is almost always messy. One of the most efficient ways to tackle this is with Polars string manipulation. In Pandas, you use .str…
