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Learn from 35+ AI experts from π§ DeepMind, Spotify, π Twitter, Disney, HuggingFace, Instacart, Colgate, π Linkedin, Pinterest, Mobileye, HSBC, AstraZeneca, Verizon, BBC and more in sessions about building real-world AI applications.
The MLCon 2.0 is meant to break down silos, to share lessons learned, pro tips, proven strategies from leading AI developers and data science leaders. Learn best practices and strategies in AI infrastructure, ML in production, and exciting research that you can apply to your next ML or DL project. Hear AI leaders as they share their successes, failures, and lessons learned so no one has to reinvent the wheel.
Get an inside look into:
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How DeepMind successfully deployed GNNs in production at Google.
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Understanding the impact of AI at Disney.
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Beyond Monitoring: Data & ML Observability in Practice.
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Spotify's lessons learned developing & operationalizing ML solutions at scale.
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How conversational AI can transform the customer and employee experience at Verizon.
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Scaling up Machine Learning in Instacart Search.
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How HSBC Apply ML to Advance Diversity and Inclusion in the Workforce.
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Data integration and AI mining in cancer treatments.
More events upcoming (free join from anywhere):
-- Feb 8, Model Accuracy With Data-centric AI Practices.
-- Feb 10, Drive Private Equity β Lessons, Trends for Data Scientists
-- Feb 10, apply(): ML and data engineering summit.
-- Feb 22~23, MLCon 2.0: The Machine Learning Conference.
-- Feb 25, MLOps workshop: Take ML Model In a Notebook to Production
-- Mar 2~3, Subsurface Live winter: ML and data lake conference.
-- Mar 10, Designing an Effective SQL Data Lakehouse
-- Mar 10, Nvidia: Federated Learning for Developing Robust AI Models
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