Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Dive into a comprehensive 51-minute podcast episode featuring Shahul Es, a data science expert and Kaggle Grandmaster, as he explores the intricacies of evaluating Large Language Model (LLM) applications. Learn about debugging techniques, troubleshooting strategies, and the challenges associated with benchmarks in open-source models. Gain valuable insights on custom data distributions, the significance of fine-tuning in improving model performance, and the Ragas Project. Discover the importance of evaluation metrics, the impact of gamed leaderboards, and strategies for recommending effective evaluation processes. Explore topics such as prompt injection, alignment, and the concept of "garbage in, garbage out" in LLM applications. Connect with the MLOps community through various channels and access additional resources, including job boards and merchandise.