Fix to broken docs pages

Author: mandar2812

docs/core/core_prob_dist.md

@@ -21,7 +21,7 @@ $$
 
 ## Distributions API
 
-The `#!scala Density[T]` and `#!scala Rand[T]` traits form the API entry points for implementing probability distributions in breeze. In the `#!scala dynaml.probability.distributions` package, these two traits are inherited by [`#!scala GenericDistribution[T]`](https://transcendent-ai-labs.github.io/api_docs/DynaML/recent/dynaml-core/io/github/mandar2812/dynaml/probability/distributions/GenericDistribution) which is extended by [`#!scala AbstractContinuousDistr[T]`](https://transcendent-ai-labs.github.io/api_docs/DynaML/recent/dynaml-core/#io.github.mandar2812.dynaml.probability.distributions.AbstractContinuousDistr) and [`#!scala AbstractDiscreteDistr[T]`](https://transcendent-ai-labs.github.io/api_docs/DynaML/recent/dynaml-core/io/github/mandar2812/dynaml/probability/distributions/AbstractDiscreteDistr) classes.
+The `#!scala Density[T]` and `#!scala Rand[T]` traits form the API entry points for implementing probability distributions in breeze. In the `[#!scala dynaml.probability.distributions`](https://transcendent-ai-labs.github.io/api_docs/DynaML/recent/dynaml-core/#io.github.mandar2812.dynaml.probability.distributions.package) package, these two traits are inherited by [`#!scala GenericDistribution[T]`](https://transcendent-ai-labs.github.io/api_docs/DynaML/recent/dynaml-core/io/github/mandar2812/dynaml/probability/distributions/GenericDistribution) which is extended by [`#!scala AbstractContinuousDistr[T]`](https://transcendent-ai-labs.github.io/api_docs/DynaML/recent/dynaml-core/#io.github.mandar2812.dynaml.probability.distributions.AbstractContinuousDistr) and [`#!scala AbstractDiscreteDistr[T]`](https://transcendent-ai-labs.github.io/api_docs/DynaML/recent/dynaml-core/io/github/mandar2812/dynaml/probability/distributions/AbstractDiscreteDistr) classes.
 
 !!! tip "Distributions which can produce confidence intervals"
     The trait [`#!scala HasErrorBars[T]`](https://transcendent-ai-labs.github.io/api_docs/DynaML/recent/dynaml-core/#io.github.mandar2812.dynaml.probability.distributions.HasErrorBars) can be used as a mix in to provide the ability of producing error bars to distributions. To extend it, one has to implement the `#!scala confidenceInterval(s: Double): (T, T)` method.

docs/core/core_stp.md

@@ -64,7 +64,7 @@ val model = new MOStudentTRegression[DenseVector[Double]](
 ```
 
 !!! tip
-		Working with multi-output Student T models is similar to [multi-output GP](/core/core_gp.html#gp-models-for-multiple-outputs) models. We need to create a kernel function over the combined index set `#!scala (DenseVector[Double], Int)`. This can be done using the _sum of separable_ kernel idea.
+		Working with multi-output Student T models is similar to [multi-output GP](/core/core_gp/#gp-models-for-multiple-outputs) models. We need to create a kernel function over the combined index set `#!scala (DenseVector[Double], Int)`. This can be done using the _sum of separable_ kernel idea.
 
 		```scala