Overview Provides hands-on exercises and real-world case studies to apply LLM and ML concepts Covers step-by-step MLFlow experiment tracking and visualization techniques Includes cutting-edge insights into the future of AI, ML, and Azure Data Lakehouses What You'll Learn Build full-stack ML and GenAI solutions on Databricks Train and track models with MLFlow, AutoML, and tuning strategies Secure and govern data with Unity Catalog Apply explainable, ethical AI techniques Deploy and monitor ML models in real-world pipelines Use RAG and vector search to power GenAI applications Gain confidence with hands-on labs and real enterprise use cases Who This Book Is For Azure administrators, data architects, and data engineers
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