Eval Engineering for AI Developers - Lesson 2 скачать в хорошем качестве

Eval Engineering for AI Developers - Lesson 2

Learn Eval Engineering in this free, 5-part, hands-on course. ​90% of AI agents don't make it successfully to production. The biggest reason is the AI engineers building these apps don't have a clear way of evaluating that these agents are doing what they should do, and using the results of this evaluation to fix them. ​In this course, you will learn all about evals for AI applications. You'll start with some out-of-the-box metrics and learn about evals, then move onto understanding observability for AI apps, analyzing failure states, defining custom metrics, then finally using these across your whole SDLC. ​This will be hands on, so be prepared to write some code, create some metrics, and do some homework! ​In this second lesson, you will Use observability to visualize the components of a typical multi-agent AI application Learn about the different components that make up these applications Apply some out-of-the-box metrics to start to get an understanding of how your application is working ​Prerequisites: ​A basic knowledge of Python ​- Access to an OpenAI API key ​- A free Galileo account (we will be using Galileo as the evals platform) Sign up for the upcoming lessons here: Lesson 3: https://luma.com/3k99shl1 Lesson 4: https://luma.com/x2ztpa4f Lesson 5: https://luma.com/esoi6izo