From Fragmented Knowledge to Unified Insights: The Power of Clean Data

Getting the data for AI right is hard! Your data might be fragmented, leaving holes in the pattern. Or you might risk over-tuning the model creating a bias in your results! Each of these common pitfalls can be overcome. The trick is doing it efficiently. Let's discuss strategies for advanced data cleaning, synthetic data generation, and bias mitigation in the context of a real-world project: call center chatbot. We'll share how it transformed legally approved yet disjointed knowledge articles into a unified training dataset. Join us for key insights into rethinking your data strategies and developing your ethical, efficient AI systems.