A recommender system toolkit with more maths functions. Currently it's only used to learn and improve about this field, but feel free to participate.
1.- Primordial: - [ ] Fix possible errors in formulas - [ ] Add tests for each formula to be sure that it's correct - [ ] Normalize documentation so is the same everywhere - [ ] Create two types of docs. One in separated .md file with extense explanation and math examples. And the second one more for "code use" - [ ] Fix typos - [ ] Create a trait for the similarities - [ ] Share this trait with the struct representing Items and Users
2.- Nice to have: - [ ] Add more docs in .md related - [ ] Add tests in the docs - [ ] Improve the code snippets. (The title can be the method's name)
3.- Final steps: - [ ] Accept incoming data - [ ] Convert incoming data into structs? - [ ] Process data and get rankings - [ ] Check ranking accuracy - [ ] Run multiples algorithms at the same time
4.- Future nice to have: - [ ] Save data and results - [ ] Create some sort of "cache" to avoid multiples recalculations - [ ] Use ndarrays of some sort of efficient sci-library
rust
/// # [Name of the concept]
/// [Small explanation of the function]
///
/// ## Parameters:
/// * `[Parameter of the function]`: [Small explanation]
///
/// ## Returns:
/// * [What does the function returns]
///
/// ## Examples:
/// [Examples]
///
/// ## Explanation:
/// [Explanation of the mathematical concept]
///
/// ## Formula:
/// $$ [Mathematical formula in raw katex format] $$
///
/// ### Where:
/// * [Definition of each component of the formula]