🚀 Meet Elemeta – Extract metafeatures from unstructured data

Events

Meet the team and learn about our ML monitoring methodologies and best practices.
Talks
Talks

Introducing Elemeta: OSS meta-feature extractor for NLP & vision

In this talk, we will introduce Elemeta, our OSS meta-feature extractor library in Python, which applies a structured approach to unstructured data by extracting information from text and images to create enriched tabular representations. With Elemeta, practitioners can utilize structured ML monitoring techniques in addition to the typical latent embedding visualizations and engineer alternative features to be utilized in simpler models such as decision trees.
May 9th, 2023 | 2:40 PM
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Talks

Retraining won’t fix your model (always)

When models misbehave, we often turn to retraining to fix the problem, but retraining is not always the best or only solution out there. In this session we'll take a crash intro in alternative techniques.
November 29th, 2022 | 9:45 AM EST
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Talks

Data-driven retraining with production insights

In this talk, we'll showcase, through ML monitoring and notebooks, how data scientists and ML engineers can leverage ML monitoring to find the best data and retraining strategy mix to resolve machine learning performance issues. This data-driven, production-first approach enables more thoughtful retraining selections, shorter and leaner retraining cycles, and can be integrated into MLOps CI/CD pipelines for continuous model retraining upon anomaly detection.
November 1st - 3rd, 2022 | San Francisco
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Talks

A Guide to Multi-Tenancy Architectures in ML

This session will cover architectural considerations for multi-tenancy in ML, best practices in traditional software engineering that can be copy/pasted over to MLOps, as well as new considerations unique to ML
October 13th, 2022 | 1:00 PM ET
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Talks

The uncommon monitoring challenges unique to Fintech

to the Fintech industry. In this keynote, our head of product, will walk you through the challenges of unbalanced use cases, adversarial attacks, and delayed feedback for Fintech companies and share our best practices on how to overcome them.
Jun 22nd - 24th, 2022 | Berlin
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Talks

Data-driven ML retraining with production insights

Don't miss, Oryan Omer, Superwise's lead software engineer talk at the ODSC in London
June 15th, 2022 | 3:30 PM - 4:00 PM
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Talks

A framework for a successful continuous training strategy

Swing by the Superwise booth and let's talk MLOps and ML monitoring.
June 9th, 2022 | 3:45 PM - 4:30 PM
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Talks

A guide to building a continuous MLOps stack

Swing by the Superwise booth and let's talk MLOps and ML monitoring.
June 10th, 2022 | 10:45 AM - 12:30 PM
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Talks

Lessons learned from ML monitoring failures

Swing by the Superwise booth and let's talk MLOps and ML monitoring.
June 9th, 2022 | 1:15 PM - 1:45 PM
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Talks

A guide to putting together a continuous ML stack

In this workshop, we’ll take a dive into MLOps CI/CD + CT pipeline automation. Part 1, we’ll focus on how to put together a continuous ML pipeline to train, deploy, monitor, and retrain your models. Part 2 will focus on automations and production-first insights to detect and resolve issues faster. This hand-on build will be...
Mar 29th, 2022 | Virtual
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Talks

MDLI Ops 2022

Join us at ‍12:20 PM for a panel on “The MLOps Stack: Where do we go from here?”. With Oren Razon (Superwise), Naama Ziporin (Outbrain), Or Hiltch (JLL)
Jan 20th, 2022 | Virtual
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