TWIMLcon 2019

TWIMLcon: AI Platforms

The 2019 Conference for platforms, tools, technologies, and practices necessary to enable and scale machine learning and AI in the enterprise.

Conference sessions now available for Free On Demand viewing!

Discover how leading organizations deliver high-velocity ML and AI at scale

Register today and get access to all of these perks with Free On Demand viewing.
50+ Worldclass ML and MLOPS Practitioners

Learn from 50+ world-class data science, ML and MLOps practitioners and leaders—from companies like Netflix, Shopify, LinkedIn, Spotify, Google, Walmart, iRobot, Adobe, Intuit, Yelp, Salesforce, Prosus, Qualcomm, and more.

50+ Hours of keynotes and presentations

Access 20+ hours of professionally produced keynotes, presentations, demos, and panels discussing the most important issues for practitioners and leaders building and deploying AI and ML at scale.

Learn and develop a plan for deploying AI at scale

Develop a practical blueprint for delivering machine learning efficiently and at scale.

Advance Your Skills and Accelerate Your Team!

Discover the state-of-the-art the practices, platforms, tools, and technologies for scaling and accelerating enterprise ML and AI.

Memorable Conference Insights

TWIMLcon 2019 keynote speakers and panelists have amazing insight for how to deploy and scale AI and ML/OPS for your organization.

Photo: Franziska Bell

If you’re serious about your data, you want to invest in your platforms.

Photo: Khari Johnson

The goal is to produce an ML system that functions reliably and that can replicate that at scale.

Photo: Eric Colson

This is the greatest technology of our lifetime, now it’s about getting the tools to be able to do it at scale

Photo: Ameen Kazerouni

The currency of an analytics team is trust, not data.

Keynote Speakers

This years keynote speakers hold positions at the top data science, ML/OPS tech companies in the world.

Landing AI
VP of Artificial Intelligence
Director of Data Science, Platforms

Featured Speakers

Experience the best of TWIMLcon 2019 On Demand, and learn from over 50 world-class speakers.

Data Scientist
Chief Analytics Officer
Orangetheory Fitness

Featured Sessions

Experience the best of TWIMLcon 2019 On Demand and get access to over 25 hours of video sessions.

Most AI/ML projects start shipping models into production, where they...
The state of artificial intelligence is continuing to advance rapidly,...
Models are the new code: while machine learning models are increasingly being used to make critical product and business decisions, the process of developing and deploying ML models remain ad-hoc. In this talk, we draw upon our experience with ModelDB and Verta to present best practices and tools for model versioning and ensure high quality of deployed ML models.
Case Study
In this talk, we will cover the journey we at Levi's undertook to go from a fully outsourced model to over a dozen internally-built Machine Learning models deployed in production that are ROI positive and that solve real business problems, in about two years, as well as challenges we've faced, key design methodologies and more
Case Study
Productionizing machine learning models in an organization is difficult. The goal of this presentation is to discuss how Kubernetes can be leveraged to train, deploy, and monitor models in production settings, as well as lessons learned from using Kubernetes to productionize machine learning workloads at 2U.
Machine learning models are increasingly being used to make critical decisions that impact people’s lives. Learn how to measure bias in your data sets & models, and how to apply the fairness algorithms to reduce bias across the machine learning pipeline.
Host of the TWIMLai Podcast

About Sam Charrington and the TWIML AI Podcast

The TWIML AI Podcast is hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Sam’s research is focused on the business and consumer application of machine learning and AI, bringing AI-powered products to market, and AI-enabled and -enabling technology platforms.