Artificial intelligence, like machine learning before it, is making big money off what I call the “sell ∀ ∃ as ∃ ∀ scam.” The scam works as follows. Build a system that solves problems, but with an important user-facing control. For AI systems like GPT-X this is “prompt engineering.” For […]
Estimated reading time: 3 minutes
From the frontmatter: We recommend this book! Deep Learning for Coders with fastai and PyTorch uses advanced frameworks to move quickly through concrete, real-world artificial intelligence or automation tasks. This leaves time to cover usually neglected topics, like safely taking models to production and a much-needed chapter on data ethics. […]
Estimated reading time: 31 seconds
Win Vector LLC’s Dr. Nina Zumel has had great success applying y-aware methods to machine learning problems, and working out the detailed cross-validation methods needed to make y-aware procedures safe. I thought I would try our hand at y-aware neural net or deep learning methods here.
Estimated reading time: 10 minutes
I am excited to share a new deep learning model performance trajectory graph. Here is an example produced based on Keras in R using ggplot2:
Estimated reading time: 1 minute