ML & DS Papers On The Go
ML & DS Papers On The Go
Andre Ye
Machine learning and data science are rapidly evolving fields. Keep on top of the latest and most fascinating advancements with this podcast.
Ep. 3 | Our Image Recognition Models Are Too Vulnerable: Strategies and Defenses Against Adversarial Attacks
Adversarial attacks can completely screw up an image recognition model's performance - without humans noticing a single difference. What are these attacks and how can we defend against them? - we'll explore papers and perspectives on this topic in this episode. View article summaries and links at the website here: http://papers-on-the-go.ml --- Send in a voice message: https://podcasters.spotify.com/pod/show/andre-ye/message
Feb 26, 2021
43 min
Ep. 2 | Deep Learning’s Million Dollar Question Pt. 2: Pruning, Lottery Tickets, and High-Performance Random Networks
How can a completely random neural network attain high performance? The answer lies in a very fascinating hypothesis - the Lottery Ticket Hypothesis - and allows us to make some very intriguing paradigm shifts in how we view neural network generalization. View article summaries and links at the website here: http://papers-on-the-go.ml --- Send in a voice message: https://podcasters.spotify.com/pod/show/andre-ye/message
Feb 20, 2021
42 min
Ep. 1 | Deep Learning’s Million-Dollar Question Pt. 1: Rethinking Generalization and Why We Should Care
Why don't neural networks overfit when they have so many parameters? It's deep learning's million-dollar question and one we'll try to get a few steps closer to answering. We'll get an introduction to the million-dollar question, get an understanding for the surprising amount of information neural networks can carry, and explore the discussion and research around Deep Double Descent phenomena. Links to the papers discussed: Understanding Deep Learning Requires Rethinking Generalization: arxiv.org/pdf/1611.03530.pdf || Reconciling modern machine learning practice and the bias-variance trade-off: arxiv.org/pdf/1812.11118.pdf || Scaling description of generalization with number of parameters in deep learning: arxiv.org/pdf/1901.01608.pdf Reach out to me at my email, [email protected], or at my LinkedIn, www.linkedin.com/in/andre-ye/. --- Send in a voice message: https://podcasters.spotify.com/pod/show/andre-ye/message
Feb 12, 2021
37 min
Trailer | Welcome to the ML & DS Papers On The Go Podcast!
Hey everyone! I'm your host, Andre Ye. I’m super excited to be starting this new podcast, ML & DS Papers on the go. It is my hope that this podcast is able to bring the most fascinating and recent advancements in machine learning and data science to your ears for easy access. I hope you'll join me in future episodes! --- Send in a voice message: https://podcasters.spotify.com/pod/show/andre-ye/message
Feb 8, 2021
3 min