When Data Stops Being Code and Starts Being C...

Also on YouTube Two AI experts who actually love the technology explain why chasing AGI might be the worst thing for AI's future—and why the current hype cycle could kill the field we're trying to save. Want to dive deeper? Head to datascienceathome.com for detailed show notes, c ...  Show more

Most companies don't have an AI problem. They have a decision-making problem. Matt Lea, founder of Schematical and CloudWarGames, has spent nearly 20 years helping tech leaders ship smarter.

In this conversation, he breaks down when AI actually makes sense, where AWS co ...

In this episode, I tackle three often conflated terms - AI, machine learning, and deep learning - to shine some light on what exactly they are. Additional materials: www.superdatascience.com/464 

Show notes: ocdevel.com/mlg/1. MLG teaches the fundamentals of machine learning and artificial intelligence. It covers intuition, models, math, languages ...

It seems like every day there's more and more machine learning problems that involve learning on text data, but text itself makes for fairly lousy inputs to machine learning algorithms.  That's why there are text vectorization algorithms, which re-format text data so it's ready f ...  Show more

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Machine learning consists of three steps: prediction, error evaluation, and learning, implemented by training algorithms on large datasets to build models that can make decisions or classifications. The primary categories of machine learning algorithms are supervised, un ...