MLOps Global Summit

The summit ended, please register to the next summit: AutoML Summit, September 3rd

Running machine learning in production is hard, with new challenges in managing models and pipeline services. The summit brings industry experts and tech leads from around the world to share practical experiences, best practices and tools/frameworks on managing machine learning in production through its lifecycle, which involves deployment, experiments at scale, versioning, monitoring, troubleshooting and more.


Deep dive tech talks, hands-on workshop, live Q&A


Real time chat with speakers and other attendees.


1000+ developers joining from 150+ cities from 50+ countries


Connect with speakers and attendees, networking before and after sessions.

who will speak


Unravel Data
Pyxeda AI
Computable Labs
Weights & Biases
what are topics


PDT (US Pacific Time, GMT-7); CET (Central European Time, GMT+2), check your local time
Block 1: EMEA, India, APAC, East Coast
  • 05:00 AM - 05:40 AM PDT (14:00~14:40 CET)
    Training and Deploying Models at Scale with BigQuery ML
    Polong Lin, Google
  • 05:50 AM - 06:30 AM PDT (14:50~15:30 CET)
    Building End-to-End ML Workflows with Kubeflow in AWS
    Antje Barth, AWS
  • 06:40 AM - 07:20 AM PDT (15:40~16:20 CET)
    ML Workflows in Production
    Roshini Johri, HSBC
  • 07:20 AM - 08:00 AM PDT (16:20~17:00 CET)
    Coffe Break
  • 08:00 AM - 08:40 AM PDT (17:00~17:40 CET)
    Build, Train, Deploy AI/ML Pipeline with BERT and SageMaker
    Chris Fregly, AWS
  • 08:50 AM - 09:30 AM PDT (17:50~18:30 CET)
    Running Abstract ML Frameworks Inside GitHub Actions
    Jon Peck, GitHub
  • 09:40 AM - 10:20 AM PDT (18:40~19:20 CET)
    Building BigQuery and ML models using Kubeflow Pipelines
    Valliappa Lakshmanan (LAK), Google
  • 10:30 AM - 11:10 AM PDT (19:30~20:10 CET)
    Explore/Exploit: Hyperparameter Tuning in Deep Learning
    Stacey Svetlichnaya, Weights & Biases
Block 2: North/South America, Europe, APAC
  • 12:00 PM - 12:40 PM PDT (21:00~21:40 CET)
    Rethinking Visual Data Management for Machine Learning
    Vishakha Gupta & Luis Remis, ApertureData
  • 12:50 PM - 01:30 PM PDT (21:50~22:30 CET)
    Building an AI-powered Digital Advisor: Challenges and Lessons Learned
    Shankar Pasupathy, NetApp
  • 01:40 PM - 02:20 PM PDT (22:40~23:20 CET)
    Productionizing Molecular ML Pipelines
    Bharath Ramsundar, Computable Labs
  • 02:30 PM - 03:10 PM PDT
    Tensorflow Extended, ML Platform for Production
    Anusha Ramesh, Google
  • 03:10 PM - 03:30 PM PDT
    Coffe Break
  • 03:30 PM - 04:10 PM PDT
    Best Practices for ML in Production
    Nisha Talagala, Pyxeda AI
  • 04:20 PM - 05:00 PM PDT
    Overcoming DataOps Hurdles to Get ML Models into Production
    Sandeep Uttamchandani, Unravel Data


How to attend the event?
We use Zoom. Please register here to receive the unique joining link and you can click it to join (in your confirmation email from zoom).
If you registered on eventbrite, you should receive the link already (check your spam folder too). if you don't receive it yet for whatever reason, please re-register here again.
If you register here but still not get the join link from zoom (it might take 5+ mins), please contact us or on slack for faster response.
Is the session recorded?
Yes. all sessions are recorded, will be available at AICamp youtube channel shortly after the event is done:
Social media?
We’ll be using the hashtag #mlops20 for the event on Twitter, Facebook and Instagram. @aicampai.
How to network?
Event social networking starts 30mins before/after the event on slack. Join slack by the invitation: , channel for this event (#mlops20)
Introduce yourself and let the rest of the attendees know what it is you're looking for. It's a space where you can discuss what problems you’re facing or what solutions you potentially have for other attendee's problems.

Organizing Team

Pyxeda AI
AICamp London
AICamp London