Evaluating and Debugging Generative AI

Overview

Delve into the complexities of managing machine learning and AI projects with our specialized course on Evaluating and Debugging Generative AI. Tackling diverse data sources, vast volumes of data, intricate models, and expansive testing and evaluation, this course is your gateway to mastering the art of Machine Learning Operations.

Learn to navigate and leverage the capabilities of the Weights & Biases platform, a tool designed to simplify your experimental tracking, data versioning, and team collaboration efforts.

Throughout this course, you will be equipped with practical skills to enhance your workflow, including:

• Instrumenting a Jupyter notebook for efficient operations
• Managing and adjusting hyperparameter configurations to optimize performance
• Logging run metrics for detailed performance analysis
• Creating a reliable system for dataset and model versioning through artifact collection
• Methodically logging experiment outcomes for transparent result tracking
• Tracing prompts and responses in Long Language Models (LLMs) to analyze complex interactions over time

Upon completion, you will possess a structured workflow designed to significantly improve productivity and fast-track your path to achieving pioneering results in the field of generative AI. This course is an invaluable asset for anyone looking to excel in Machine Learning and AI development, provided independently under the categories of Generative AI Courses and Jupyter Notebooks Courses.

Taught by

Carey Phelps

Subjects