This is a machine-learning-focused Podcast, where we interview people in the field of Artificial Intelligence and discuss interesting technical topics of Machine Learning. In the episodes, we focus on business-related use-cases (especially with Deep Learning ) and we also try to bring some technical white papers to the ground, not forgetting on the way that there are always some people behind the technology, so we try to understand their motivation and drive.
http://mlcafe.libsyn.com/website
episode 2: Can we predict the accuracy of a Neural Network? Yes, with the WeightWatcher tool by Charles Martin, Ph.D. - 002
In this Episode we talked about the deep neural networks and the spectral density of each layer's weights. It turns out, you can predict the accuracy ( and many more) with the WeigthWatcher application. We talk about the 5+1 Phases of learning and Heavy Tailed Self Regularization.
Charles Martin, PhD on LinkedIn:
https://www.linkedin.com/in/charlesmartin14/
During the episode we talked about these
VC Theory:
https://en.wikipedia.org/wiki/Vapnik%E2%80%93Chervonenkis_theory
Why Deep Learning works? post by Charles Martin, 2015
https://calculatedcontent.com/2015/03/25/why-does-deep-learning-work/
Presentation at Berkeley: Why Deep Learning works? by Charles Martin, 2016
https://www.youtube.com/watch?v=fHZZgfVgC8U
Several Papers written by Charles Martin and Michael Mahoney:
https://arxiv.org/search/?query=%22Charles+H.+Martin%22&searchtype=author&abstracts=show&order=-announced_date_first&size=50
Newest blog post about weightwatcher, 2019 December:
https://calculatedcontent.com/2019/12/03/towards-a-new-theory-of-learning-statistical-mechanics-of-deep-neural-networks/
WeightWatcher on GitHub:
https://github.com/CalculatedContent/WeightWatcher
easy installation for python users:
pip install weightwatcher
How to reach out:
https://calculationconsulting.com/
charles@calculationconsulting.com
To access their slack channel please contact Charles first.
---Copyright Info---
Music is from https://filmmusic.io , intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)