What is machine learning and how can it be connected to prior scientific knowledge (SciML)?
Machine learning is the process of learning functions. In this talk we introduce what neural networks are at a high level and use that as an introduction to scientific machine learning (SciML), the discipline that is improving machine learning by incorporating prior scientific knowledge into the neural architectures.

▶︎
What is (scientific) machine learning? An introduction through Julia's Lux.jl

▶︎
Math's Fundamental Flaw

▶︎
How AI Cracked the Protein Folding Code and Won a Nobel Prize

▶︎
Yann LeCun: World Models: Enabling the next AI revolution

▶︎
The World's Most Important Machine

▶︎
Historian Timothy Snyder on ENDING Trump Nightmare FOR GOOD | PoliticsGirl

▶︎
Putin's Army Is Running Out Of LOYALTY

▶︎
The Standard Model of Particle Physics: A Triumph of Science

▶︎
What do tech pioneers think about the AI revolution? - The Engineers, BBC World Service

▶︎
What is SonarQube | Introduction SonarQube | SonarQube Tutorial | SonarQube Basics | Intellipaat

▶︎
The Riemann Hypothesis, Explained

▶︎
How ASML Makes Chips Faster With Its New $400 Million High NA Machine

▶︎
AlphaFold - The Most Useful Thing AI Has Ever Done

▶︎
🩸Phlebotomy Certification Practice Test – 50 Questions to Help You PASS!

▶︎
How to Build & Sell AI Agents: Ultimate Beginner’s Guide

▶︎
6 Tips on Being a Successful Entrepreneur | John Mullins | TED

▶︎
Model Discovery w/ Imposed Structures and Prior Knowledge Scientific Machine Learning | ML4Science

▶︎
But what is a neural network? | Deep learning chapter 1

▶︎
RL for Agents Workshop - Deep Dive on Training Agents with RL and Open Source

▶︎
