Running Any ML Code in Any ML Framework - Ivy Introduction

Explore the motivation, design, and applications of Ivy as a framework-agnostic ML solution in this PyData SoCal guest talk. Dive into Ivy's core functionalities, its role in addressing the ML framework explosion, and its potential as a universal docking station for machine learning. Learn how Ivy works as both a standalone framework and a transpiler, enabling the execution of ML code across different frameworks. Discover practical demonstrations of function, library, and model transpilation. Gain insights into Ivy's design principles and its impact on the ML ecosystem. Engage with Q&A sessions throughout the talk to deepen your understanding of this innovative approach to machine learning development.

Intro
Ivy in a Nutshell - What does Ivy do?
Ivy in a Nutshell - How does Ivy work?
Questions
The ML Stack - Framework Explosion
The ML Stack - What does Ivy add?
Questions
Ivy Design
Questions
Ivy as a Framework
Questions
Ivy as a Transpiler - Transpiling Functions
Questions
Ivy as a Transpiler - Transpiling Libraries
Ivy as a Transpiler - Transpiling Models
Questions
A Universal Docking Station
Our Growing Team