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Speaker "Robert Crowe" Details Back

 

Topic

TFX: Production ML Pipelines with TensorFlow Workshop

Abstract

Putting machine learning models into production is now mission critical for every business - no matter what size. 
 
TensorFlow is the industry-leading platform for developing, modeling, and serving deep learning solutions.  But putting together a complete pipeline for deploying and maintaining a production application of AI and deep learning is much more than training a model.  Google has taken years of experience in developing production ML pipelines and offered the open source community TensorFlow Extended (TFX), an open source version of tools and libraries that Google uses internally.
 
Learn what’s involved in creating a production pipeline, and walk through working code in an example pipeline with experts from Google.  You’ll be able to take what you learn and get started on creating your own pipelines for your applications.
 
Who is this presentation for?
Developers who are currently or planning to put machine learning applications into production.
 
Prerequisite knowledge
Basic understanding of machine learning and software development in Python
 
What you'll learn?
Issues and best practices for putting ML applications into production.  Hands on experience using TensorFlow Extended (TFX) to create a production pipeline.
 
Requirements
Access to a MacOS or Linux system with Python 3, Virtualenv, and Git installed

 

Profile

A recovering data scientist and TensorFlow addict, Robert has a passion for helping developers quickly learn what they need to be productive.  He's used TensorFlow since the very early days and is excited about how it's evolving quickly to become even better than it already is.  Before moving to data science Robert led software engineering teams for both large and small companies, always focusing on clean, elegant solutions to well-defined needs.  In his spare time Robert surfs, sails, and raises a family.