[Exclusive] Weights & Biases Round-table // Model Management in a Regulated Environment

MLOps Coffee Sessions Special episode with Weights & Biases, Model Management in a Regulated Environment, fueled by our Premium Brand Partner, Weights & Biases. // Abstract Step into the fascinating world of Language Model Management (LLMs) in a Regulated Environment! Join us for an enlightening chat where we'll explore the intricacies of managing models within highly regulated settings, focusing on compliance and effective strategies. This is your opportunity to be part of a dynamic conversation that delves into the challenges and best practices of Model Management in Regulated Environments. Secure your spot today and stay tuned for an enriching dialogue on navigating the complexities of navigating the regulated terrain. Don't miss out on the chance to broaden your understanding and connect with peers in the field! // Bio Darek Kłeczek Darek Kłeczek is a Machine Learning Engineer at Weights & Biases, where he leads the W&B education program. Previously, he applied machine learning across supply chain, manufacturing, legal, and commercial use cases. He also worked on operationalizing machine learning at P&G. Darek contributed the first Polish versions of BERT and GPT language models and is a Kaggle Competitions Grandmaster. Mark Huang Mark is a co-founder and Chief Architect at Gradient, a platform that helps companies build custom AI applications by making it extremely easy to fine-tune foundational models and deploy them into production. Previously, he was a tech lead in machine learning teams at Splunk and Box, developing and deploying production systems for streaming analytics, personalization, and forecasting. Prior to his career in software development, he was an algorithmic trader at quantitative hedge funds where he also harnessed large-scale data to generate trading signals for billion-dollar asset portfolios. Oliver Chipperfield Oliver Chipperfield is a Senior Data Scientist and Team Lead at M-KOPA, where he utilizes his expertise in machine learning and data-driven innovation. At M-KOPA since October 2021, Oliver leads a diverse tech team, making improvements in credit loss forecasting and fraud detection. His career spans multiple industries, where he has applied his extensive knowledge in Python, Spark, R, SQL, and Excel. He also specialized in the building and design of production ML systems, experimentation, and Bayesian statistics. Michelle Marie Conway As an Irish woman who relocated to London after completing her university studies in Dublin, Michelle spent the past 12 years carving out a career in the data and tech industry. With a keen eye for detail and a passion for innovation, She has consistently leveraged my expertise to drive growth and deliver results for the companies she worked for. As a dynamic and driven professional, Michelle is always looking for new challenges and opportunities to learn and grow, and she's excited to see what the future holds in this exciting and ever-evolving industry. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links Fine-Tuning LLMs: Best Practices and When to Go Small // Mark Kim-Huang // MLOps Meetup #124 - https://youtu.be/1WSUfWojoe0 --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Darek on LinkedIn: https://www.linkedin.com/in/kleczek/ Connect with Mark on LinkedIn: https://www.linkedin.com/in/markhng525/ Connect with Oliver on LinkedIn: https://www.linkedin.com/in/oliver-chipperfield/ Connect with Michelle on LinkedIn: https://www.linkedin.com/in/michelle-conway-40337432

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Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.