I'm aiming to setup a space for more interactive UX experiments. My current Hugo blog has held up well with my scale of content but doesn't play nicely with modern Javascript frameworks, where most of the open source energy is currently invested.
In this notebook, we'll use the MovieLens 10M dataset and collaborative filtering to create a movie recommendation model. We'll use the data from movies.dat and ratings.dat to create embeddings that will help us predict ratings for movies I haven't watched yet.
I've started posting more on Bluesky and I noticed that articles from my site didn't have social image previews 😔
I explored how embeddings cluster by visualizing LLM-generated words across different categories. The visualizations helped build intuition about how these embeddings relate to each other in vector space. Most of the code was generated using Sonnet.
Language models are more than chatbots - they're tools for thought. The real value lies in using them as intellectual sounding boards to brainstorm, refine and challenge our ideas.
Using Cursor, we can easily get a first pass at creating alt text for an image using a language model. It's quite straightforward using a multi-modal model/prompt. For this example, we'll use claude-3-5-sonnet-20241022.
Having completed lesson 5 of the FastAI course, I prompted Claude to give me some good datasets upon which to train a random forest model. This housing dataset from Kaggle seemed like a nice option, so I decided to give it a try. I am also going to try something that Jeremy Howard recommended for...
In this notebook/post, we're going to be using the markdown content from my blog to try a language model. From this, we'll attempt to prompt the model to generate a post for a topic I might write about.
I recently found Joe's article, We All Know AI Can’t Code, Right?.
I had the idea to try and use a language model as a random number generator. I didn't expect it to actually work as a uniform random number generator but was curious to see what the distribution of numbers would look like.