> For the complete documentation index, see [llms.txt](https://fall2019.fullstackdeeplearning.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://fall2019.fullstackdeeplearning.com/course-content/setting-up-machine-learning-projects/baselines.md). # Baselines {% embed url="" %} Baselines - ML Projects {% endembed %} * A **baseline** is a model that is both simple to set up and has a reasonable chance of providing decent results. It gives you a lower bound on expected model performance. * Your choice of a simple baseline depends on the kind of data you are working with and the kind of task you are targeting. * You can look for **external baselines** such as business and engineering requirements, as well as published results from academic papers that tackle your problem domain. * You can also look for **internal baselines** using simple models and human performance. * There is a tradeoff between cost and quality when designing human baselines. More specialized domains require more skilled labelers, so you should find cases where the model performs worse and concentrate the data collection effort there. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://fall2019.fullstackdeeplearning.com/course-content/setting-up-machine-learning-projects/baselines.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.