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Best Practices for Data Preparation in Generative AI Development

Offered By: Databricks via YouTube

Tags

Generative AI Courses Machine Learning Courses Data Cleaning Courses Data Transformation Courses Data Preparation Courses Data Preprocessing Courses Data Normalization Courses Data Labeling Courses

Course Description

Overview

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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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