ML

Over the past few years Atlanta’s tech scene has grown at a rapid pace. There was no better place for proof of this than at RenderATL 2024.

As industry races for use cases of Large Language Models, software devs have emerged as early adopters. Can LLMs help us translate between tech and talk? Let’s build a text-to-SQL application with Vanna and Streamlit!

Sick of hearing about hyped up AI solutions that sound like hot air? 🧐 Let’s use boring old ML to detect hype in AI marketing text and see why starting with a simple ML approach is still your best bet 90% of the time.

We’re seeing a proliferation of Large Language Models (LLMs) as companies seek to replicate OpenAI’s success. In this post, two AI engineers respond to LLM FAQs and offer tips for responsible innovation.

Over the years, several JavaScript libraries have been created for machine learning. Let’s sort through the ones that can help you get started quickly, even if you don’t have much experience with machine learning or data …

Move over ChatGPT, here come the Large Language Models (LLMs). More and more companies are incorporating LLMs into their operations. Are you ready? Here’s the guide to how Rotational plans and scopes our LLM projects.

The last few years have marked a shift in industry away from research-oriented machine learning. These days, shipping models early and often is critical, and open source tools like Prefect can speed up the process of operationalizing ML.

Like any new tool, Ensign takes a little time to learn. But take it from us (a bunch of seasoned data science experts) – it will open up a new world of data science applications for you. Check out this beginner-friendly introduction!

Most of us got into data science because it’s exciting (if chaotic) and there’s a constant stream of new ideas, which is thrilling (if intimidating). But if learning is all about keeping up, why can’t our models do it?