fix broken @ref links in docs

Author: tiemvanderdeure

docs/src/usage/mlj.md

@@ -7,14 +7,13 @@ Maxnet.jl integrates with the MLJ ecosystem.
 
 See [MLJs project page](https://github.com/alan-turing-institute/MLJ.jl) for more info about MLJ.
 
-To use Maxnet with MLJ, initialise a model by calling [`MaxnetBinaryClassifier`](@ref), which accepts any arguments otherwise passed to [`maxnet`]. The model can then be used to construct MLJ's `machine`.
+To use Maxnet with MLJ, initialise a model by calling [`MaxnetBinaryClassifier`](@ref), which accepts any arguments otherwise passed to [`maxnet`](@ref). The model can then be used with MLJ's `machine`.
 
 For example:
 
 ```julia
 using Maxnet: MaxnetBinaryClassifier, bradypus
 using MLJBase
-using CategoricalArrays
 
 # sample data
 y, X = bradypus()
@@ -38,4 +37,3 @@ pred_test = predict(mach; rows = test)
 pred = predict(mach, X)
 ```
 
-

docs/src/usage/quickstart.md

@@ -26,7 +26,7 @@ bradypus_model = maxnet(p_a, env)
 prediction = predict(bradypus_model, env)
 ```
 
-There are numerous settings that can be tweaked to change the model fit. These are documentated in the documentation for the `maxnet`(@ref) and `predict`(@ref) functions.
+There are numerous settings that can be tweaked to change the model fit. These are documentated in the documentation for the [`maxnet`](@ref) and [`predict`](@ref) functions.
 
 ### Model settings
 The two most important settings to change when running Maxnet is the feature classes selected and the regularization factor.