Issued 23 May 2025
Enhanced AI Stringency: Learn the theory of prompt temperature settings to create parameters for LLM responses Decision-Tree-Style Prompting: Learn how to leverage binary decision trains to execute multi-class document classification using an LLM AI Self-Reflection: Understand the core concepts of AI self-reflection to be able to self-evaluate and minimize hallucinations. Multi-stage Solution Architecture: See how to integrate an LLM with key data sources to create a holistic system
Understanding Generative AI in Women's Health: Learn how Generative AI can identify and address biases in women's health research. Enhancing Systematic Review Processes: Discover methods to speed up systematic reviews and improve decision-making governance. Challenges and Best Practices in LLM Training: Understand the difficulties in training large language models and best practices to reduce biases. Conceptualizing Multi-Class Classification Models: Explore the development of classification models, focusing on AI self-reflection, accuracy, and human input. Improving AI Governance and Decision-Making: Learn strategies to ensure ethical and effective use of AI in decision-making processes.
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