Data

While the internet is an endless source of free data, everyone is training on the same tired datasets, and they’ve likely got more years of practice. Building a novel dataset tailored to your problem can be a game-changer (if done right).

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.

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.

Python may be the 2nd best language for everything, but it’s a favorite of data scientists worldwide, and delivers a world of functionality. Did you know you can even build customer-facing AI/ML apps with Python now? Learn how…

Dataframes are a powerful data structure for data processing, analytics, and ML. For many years, Pandas has been my go-to. But it can really slow you down when you’re working with big or high-dimensional data. Enter Polars!