Explainerdashboard

New Features
- Static html export! You can export a static version of the dashboard using the default values
that you specified in the components or through kwargs with `dashboard.to_html()`.
- for custom components you need to define your own custom `to_html()` methods, see the documentation.
- A toggle is added to the dashboard header that allows you to download a static export
of the current live state of the dashboard.
- adds a new toggle and parameter to the ConfusionmatrixComponent to either average
the percentage over the entire matrix, over the rows or over the columns.
Set normalize='all', normalize='true', or normalize='pred'.
- also adds a `save_html(filename)` method to all `ExplainerComponents` and `ExplainerDashboard`
- `ExplainerHub` adds a new parameter `index_to_base_route`:
Dispatches Hub to `/base_route/index` instead of the default `/` and `/index`.
Useful when the host root is not reserved for the ExplainerHub

New Features
- adds support for `PyTorch` Neural Networks! (as long as they are wrapped by `skorch`)
- adds `SimplifiedClassifierComposite` and `SimplifiedRegressionComposite` to `explainerdashboard.custom`
- adds flag `simple=True` to load these simplified one page dashboards: `ExplainerDashboard(explainer, simple=True)`
- adds support for visualizing trees of `ExtraTreesClassifier` and `ExtraTreesRegressor`
- adds `FeatureDescriptionsComponent` to `explainerdashboard.custom` and the Importances tab
- adds possibility to dynamically add new dashboards to running ExplainerHub using `/add_dashboard` route
with `add_dashboard_route=True` (will only work if you're running the Hub as a single worker/node though!)

Improvements
- `ExplainerDashboard.to_yaml("dashboards/dashboard.yaml", dump_explainer=True)`
will now dump the explainer in the correct subdirectory (and also default
to explainer.joblib)
- Interactions tab automatically excluded for linear models

Bug Fixes
- Fixes incompatibility bug with dtreeviz >= 1.3
- Fixes ExplainerHub dbc.Jumbotron style bug

Improvements
- raises ValueError when passing `shap='deep'` as it is not yet correctly supported

Fixes a bug with removing outliers when nan's are present.