USENIX Conference on Operational Machine Learning (OpML)

July 28th, 2020
ElevateIT

 July 28th, 2020 - August 7th, 2020 

USENIX Conference on Operational Machine Learning (OpML)

Event submitted on Friday, August 14th 2020, approved by Charles Villanueva

USENIX Conference on Operational Machine Learning (OpML), July 28th, 2020Click to Tweet

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July 28th, 2020 - August 7th, 2020
United States  »  West, USA  »  California » 
Event Website

This event has been tagged as follows:

* This is an online event (webinar)
This event is part of a series managed by USENIX Association

 Our Review

We cover a lot of Machine Learning events in our directory, in fact we have a dedicated “recommended Machine Learning conferences” resource. Clearly, if you work in the space then this virtual conference would be a fantastic idea to attend and participate in.

- Review written by Henry Dalziel on Friday, August 14th 2020.
- Would you like to edit this review? You can by sending us a message or you can connect through LinkedIn.

Event Summary

The following description was either submitted by the Conference Organizer on Friday, August 14th 2020, or created by us.

Machine learning (ML), with its variants (deep learning (DL), reinforcement learning, and more) is impacting every commercial industry. The 2019 Conference on Operational Machine Learning was an energetic gathering of industry experts, practitioners, and researchers who came together to explore the critical challenges associated with bringing Machine Learning to Production. For this 2020 edition of the conference, OpML will continue this focus on operational machine learning and its variants and will focus on managing ML into production and the full lifecycle of deploying.

OpML ’20 will gather systems researchers, machine learning and practitioners under one roof to bring to practice and develop cutting-edge solutions and impactful research advances to the pervasive challenges of ML production lifecycle management. OpML is complementary to existing conferences that focus on algorithmic advances and systems design for improved ML methods, performance, and scale. OpML focuses on deployment, orchestration, automation, monitoring, compliance, diagnostics, governance, re-training, and production scale training.

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