We introduce the weightwatcher (ww) , a python tool for a python tool for computing quality metrics of trained, and pretrained, Deep Neural Netwworks. pip
Towards a new Theory of Learning: Statistical Mechanics of Deep Neural Networks
Introduction For the past year or two, we have talked a lot about how we can understand the properties of Deep Neural Networks by examining
This Week in Machine Learning and AI: Implicit Self-Regularization
Big thanks to and the team at This Week in Machine Learning and AI for my recent interview: https://twimlai.com/meetups/implicit-self-regularization-in-deep-neural-networks/
SF Bay ACM Talk: Heavy Tailed Self Regularization in Deep Neural Networks
My Collaborator did a great job giving a talk on our research at the local San Francisco Bay ACM Meetup Michael W. Mahoney UC Berkeley
Heavy Tailed Self Regularization in Deep Neural Nets: 1 year of research
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
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
