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DTSTART;TZID=America/New_York:20240723T120000
DTEND;TZID=America/New_York:20240723T124500
DTSTAMP:20260424T185242
CREATED:20240710T163419Z
LAST-MODIFIED:20240710T163419Z
UID:4575-1721736000-1721738700@www.mdtechcouncil.com
SUMMARY:Unlocking the Power of AI and Machine Learning with Databricks: Strategies\, Tools\, and Best Practices
DESCRIPTION:AI and LLM Solutions Building on Databricks: key concepts of the end-to-end AI lifecycle\, from data preparation and model building to deployment\, monitoring\, and MLOps \n• Data preparation for model training: Learn how to load and process data for AI workloads.\n• Feature engineering: Use Unity Catalog to create feature tables and track feature lineage.\n• Training and registration of models: Use AutoML for efficient training and tuning of ML models.\n• Production real-time or batch serving: Start using model serving for real-time workloads or deploy MLflow models for offline inference.\n• Self-hosting large language models (LLMs): Securely and cost-effectively host open-source LLMs within the Databricks environment.\n• Monitoring deployed models: Continuously capture and log Model Serving endpoint inputs and predictions.\n• Bundle assets for programmatic deployment: Use Databricks Asset Bundles for efficient packaging and deployment of data and AI assets.\n• End-to-end MLOps: Combine DataOps\, ModelOps\, and DevOps for end-to-end ML and LLM operations.\n• Build LLM-powered RAG solutions: Leverage enterprise data to create accurate Q&A chatbots. \n
URL:https://www.mdtechcouncil.com/membership/events/calendar/unlocking-the-power-of-ai-and-machine-learning-with-databricks-strategies-tools-and-best-practices/
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