LLM Evaluations and Grounding Techniques
LLM Evaluations and Grounding Techniques
Duration: 2h 44m 12s | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 433 MB
Genre: eLearning | Language: English
Duration: 2h 44m 12s | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 433 MB
Genre: eLearning | Language: English
Are you looking to learn more about large language models (LLMs)? Join instructor Denys Linkov as he explores hallucinations, their causes, the implications they have on the reliability and usability of LLMs, and how to mitigate structural and contextual inaccuracies to ensure high-quality, time-sensitive output. Develop practical techniques for addressing hallucinations, including few-shot learning, model fine-tuning, and templates for guiding LLM outputs. You'll also delve into more advanced topics like the chain of thought reasoning, retrieval-augmented generation, and model routing to enhance LLM performance. Test out your new skills along the way with real-world challenges that provide hands-on experience to solidify your learning. Whether you’re an AI researcher, a data scientist, or a tech enthusiast intrigued by the evolving capabilities of LLMs, this course offers valuable insights on navigating the complexities of AI with ease.
More Info