In this episode I briefly explain the concept behind activation functions in deep learning. One of the most widely used activation function is the rectified linear unit (ReLU). While there are several flavors of ReLU in the literature, in this episode I speak about a very interesting approach that keeps computational complexity low while improving performanc ... Show More
Nov 2022
The practicalities of releasing models
Recently Chris and Daniel briefly discussed the Open RAIL-M licensing and model releases on Hugging Face. In this episode, Daniel follows up on this topic based on some recent practical experience. Also included is a discussion about graph neural networks, message passing, and tw ... Show More
37m 19s
May 2018
Practical Deep Learning with Rachel Thomas - TWiML Talk #138
In this episode, i'm joined by Rachel Thomas, founder and researcher at Fast AI. If you’re not familiar with Fast AI, the company offers a series of courses including Practical Deep Learning for Coders, Cutting Edge Deep Learning for Coders and Rachel’s Computational Linear Algeb ... Show More
44m 19s
Mar 2025
180: Reinforcement Learning
Patrick and Jason introduce reinforcement learning and place it alongside supervised and unsupervised learning. They cover Q-learning, SARSA, policy gradients, actor-critic methods, PPO, imitation learning, and why training and evaluating RL systems is so challenging.
1h 52m
May 2025
Hugging Face Explained: The AI Toolkit Everyone’s Talking About
In this episode we cover Hugging Face—what it is, why it matters, and how it's powering some of the biggest AI models today. We’ll break down their open-source tools, transformers library, and how developers and companies are using them to build the future of AI.“AI Hustle” PODCA ... Show More
12m 11s
