Un-biased and relevant
As a data scientist at an AI startup, you are developing an LLM to improve the company's chatbot capabilities. The success of this project depends heavily on your understanding of various factors that influence the performance and accuracy of the model.
These factors include data bias and data quality and labeling. You will present various scenarios and situations related to the data handling and training processes, and you'll need to identify the primary concept at play in each case in the meeting with the company's Chief Technology Officer (CTO).
This exercise is part of the course
Large Language Models (LLMs) Concepts
Hands-on interactive exercise
Turn theory into action with one of our interactive exercises
