Best Practices for Data Preparation in Generative AI Development
Offered By: Databricks via YouTube
Course Description
Overview
Explore best practices for data preparation in generative AI development in this 19-minute talk by Brian Kihoon Lee, Senior Software Engineer at Databricks. Discover the critical importance of data quality, diversity, and labeling for training high-performing generative AI models. Learn techniques for data preprocessing, including cleaning, normalization, and transformation, optimized specifically for generative AI. Gain practical tips and guidelines for implementing these best practices in real-world projects. Whether you're a data scientist, machine learning engineer, or AI researcher, acquire valuable insights to enhance your generative AI development process. Access additional resources like the LLM Compact Guide and Big Book of MLOps to further expand your knowledge in this field.
Syllabus
Best Practices for Data Prep for GenAI Development
Taught by
Databricks
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