ABOUT THE TALK: Building and curating representative datasets is crucial for accurate ML systems. Monitoring metrics post-deployment helps improve the model. Unstructured language models may face data shifts, leading to unpredictable inferences. Open-source APIs and annotation tools streamline annotation and reduce analyst workload.

This talk discusses generating datasets and real-time precision/recall splits to detect data shifts, prioritize data collection, and retrain models.

ABOUT THE SPEAKER: Ivan Aguilar is a data scientist at Teleskope focused on building scalable models for detecting PII/PHI/Secrets and other compliance related entities within customers' clouds. Prior to joining Teleskope, Ivan was a ML Engineer at Forge.AI, a Boston based shop working on information extraction, content extraction, and other NLP related tasks.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: While we will never replace human to human interaction for crisis intervention, there are plenty of opportunities to build intelligence with AI/ML models that crisis responders could greatly benefit from.

In this talk Maddie Schults and Mateo Garcia introduce their conversation simulator, a tool that we built leveraging openAI's API that allows them to train crisis responders on how to support people in crisis with close to real life situations and can help reduce anxiety for new crisis responders as they log on the platform for the first time.

ABOUT THE SPEAKERS: Maddie Schults is the General Manager at Crisis Text Line. She is a product leader and technologist with over 20 years of experience envisioning, building and launching enterprise software products. At Crisis Text Line, Maddie is responsible for building the Global Product for crisis care intervention and its adoption globally in different countries and languages.

Mateo Garcia is Lead Data Scientist at Crisis Text Line, where he oversees all the Analytics & Data Science efforts. He is a data leader with +7 industry experience scaling data teams from the ground up and building data products at different start-ups and consulting firms.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: In this talk, we'll dive into one of the newest Apache Arrow subprojects, Arrow Database Connectivity (ADBC), an API specification for Arrow-based database access.

Over the course of this session, you’ll get a crash course in ADBC and learn how it communicates with different data APIs (like Arrow Flight SQL and Postgres) using Arrow-native in-memory data. By the end, you’ll understand the use cases it can conquer and know where to access the resources you need to get started.

This talk will cover goals, use-cases, and examples of using ADBC to communicate with different Data APIs (such as Flight SQL or postgres) with Arrow Native in-memory data.

ABOUT THE SPEAKER: Matthew Topol is a committer for the Apache Arrow project, frequently enhancing the Golang Arrow and Parquet libraries among other enhancements and helping to grow the Arrow Community. Recently, Matt has joined Voltron Data in order to work on the Apache Arrow libraries full time and grow the Arrow Golang community. In June 2022, Matt's first book was published, which is the first (and currently only) book on Apache Arrow titled "In-Memory Analytics with Apache Arrow".

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: Hugging Face Transformers is a popular open-source project with cutting-edge Machine Learning (ML). Still, meeting the computational requirements for advanced models it provides often requires scaling beyond a single machine. This session explores the integration between Hugging Face and Ray AI Runtime (AIR), allowing users to scale their model training and data loading seamlessly. We will dive deep into the implementation and API and explore how we can use Ray AIR to create an end-to-end Hugging Face workflow, from data ingest through fine-tuning and HPO to inference and serving.

ABOUT THE SPEAKERS: Jules S. Damji is a lead developer advocate at Anyscale Inc, an MLflow contributor, and co-author of Learning Spark, 2nd Edition. He is a hands-on developer with over 25 years of experience and has worked at leading companies, such as Sun Microsystems, Netscape, @Home, Opsware/LoudCloud, VeriSign, ProQuest, Hortonworks, and Databricks, building large-scale distributed systems.

Antoni Baum is a software engineer at Anyscale, working on Ray Tune, XGBoost-Ray, Ray AIR, and other ML libraries. In his spare time, he contributes to various open source projects, trying to make machine learning more accessible and approachable.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/

ABOUT THE TALK: At Lyft, Mark Grover built the Amundsen data catalog so data scientists could navigate hundreds of thousands of tables to distinguish trustworthy data from sandboxed, out-of-date data. When he took Amundsen open source, he helped dozens of data teams support a variety of demands to make data discoverable and self-serve. Mark frequently sees processes that seem “good enough” come back to bite data teams. In this talk, Mark takes us deep into query logs and APIs to see where all of that metadata lives, and he'll demonstrate how to use it so you don’t lose any fingers during your next data change.

ABOUT THE SPEAKER: Mark Grover is the co-founder/CEO of Stemma - a modern data catalog for building self-serve data culture used by Grafana, iRobot, SoFi, Convoy and many others. He is the co-creator of the leading open-source data catalog, Amundsen, used by Lyft, Instacart, Square, ING, Snap and many more! ​Mark was previously a developer on Apache Spark at Cloudera and is a committer and PMC member on a few open-source Apache project. He is a co-author of Hadoop Application Architectures.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/