My talk at ICSI-the International Computer Science Institute at UC Berkeley. ICSI is a leading independent, nonprofit center for research in computer science. Why Deep
Author: Charles H Martin, PhD
Machine Learning Enthusiast and Consultant
Don’t Peek part 2: Predictions without Test Data
This is a followup to a previous post: DON’T PEEK: DEEP LEARNING WITHOUT LOOKING … AT TEST DATA The idea…suppose we want to compare 2
Machine Learning and AI for the Lean Start Up
Machine Learning and AI for the Lean Start Up My recent talk at the French Tech Hub Startup Accelerator
Don’t Peek: Deep Learning without looking … at test data
What is the purpose of a theory ? To explain why something works. Sure. But what good is a theory (i.e VC) that is totally
Rank Collapse in Deep Learning
We can learn a lot about Why Deep Learning Works by studying the properties of the layer weight matrices of pre-trained neural networks. And, hopefully,
Power Laws in Deep Learning 2: Universality
Power Law Distributions in Deep Learning In a previous post, we saw that the Fully Connected (FC) layers of the most common pre-trained Deep Learning
