Explore the concept of unifying machine learning with a single line of code in this technical lecture from ODSC West 2022. Dive into the motivation behind Ivy, its design, and its application as a framework-agnostic ML framework. Learn about Ivy's capabilities in transpiling functions, libraries, and models through detailed explanations and demonstrations. Discover how Ivy addresses the framework explosion in the ML stack and its potential as a universal docking station for machine learning. Gain insights into the growing team behind Ivy and hear answers to questions about graph optimization and intermediate graph exportation.
Unifying Machine Learning with One Line of Code - Ivy Framework Introduction
Overview
Syllabus
Intro
Ivy in a Nutshell - What does Ivy do?
Ivy in a Nutshell - How does Ivy work?
The ML Stack - Framework Explosion
The ML Stack - What does Ivy add?
Ivy Design
Ivy as a Framework
Ivy as a Transpiler
Ivy as a Transpiler - Transpiling Functions
Ivy as a Transpiler - Transpiling Libraries
Ivy as a Transpiler - Transpiling Models
A Universal Docking Station
Our Growing Team
Questions - After the target graph is generated are there any optimizations on top of it?
Questions - Have you considered exporting the intermediate graph into a format that can be read into another tool?
Taught by
Unify
