Joining DataFrames in Polars: The Blazing Fast join() Method
In Pandas, you use pd.merge() to combine datasets. In Polars, you use the join() method, which is one of the fastest in any library. If…
AI Project: Text Classification with Hugging Face (The Manual Way)
The Hugging Face pipeline is great for simple tasks, and it’s particularly well-known for Hugging Face Text Classification. But what if you need the raw…
Full-Stack Python: A PyScript Dashboard with Hugging Face & Polars
This is the future. Our dashboard will showcase how you can combine PyScript, Hugging Face, and Polars to create advanced data apps. We are going…
AI Project: Text Generation with gpt-2 (Hugging Face)
We’ve used the Hugging Face pipeline to understand text (sentiment-analysis) and answer questions (question-answering). Now, let’s use it for its most famous task: Text Generation….
Master Polars: A Guide to the Expression API (select, filter, with_columns)
In our Polars vs. Pandas article, we showed that Polars is faster. The reason it’s faster is its Expression API. In this article, we’ll take…
AI Project: Build a Question-Answering Bot with Hugging Face
We’ve used the Hugging Face pipeline to understand emotion and summarize text. Now, let’s use it to find answers. “Question-Answering” models are trained to read…
AI Project: Build a Text Summarizer with Hugging Face
In our last AI project, we taught Python how to understand emotion. Now, let’s teach it how to read and summarize a long article for…
PyScript for Data Science: How to Use Pandas & Matplotlib in HTML
You’ve learned how PyScript can run Python in a browser and how to interact with the page. Now, let’s do something powerful. In this article,…
Beyond the Pipeline: Loading Hugging Face Models and Tokenizers
The pipeline() function in our Hugging Face intro is amazing, but it’s a black box. To do advanced work (like fine-tuning or getting raw data),…
How to Fix: RuntimeError: CUDA out of memory (PyTorch & Hugging Face)
This is the most common—and most frustrating—error when you start working with real AI models. It means: “This AI model is too big to fit…
