Support dynamic calculations on trained model

We should be able to support different kinds of dynamic calculations on the trained model.
At the moment some of these operations are exposed as methods on the model found inside the result object.

One example is the exploration of the model's representation of a single point in https://github.com/novonordisk-research/ProcessOptimizer/blob/develop/examples/7Dimensional_optimization_and_plotting.ipynb where the following code is executed to generate further data
```python
samples_of_y = res.models[-1].sample_y(transformed_point, n_samples=25000, random_state=None)`
```
These calculations has to be made on the server as it is the only place we have access to python. The solution currently pursued is to send the pickled result from #6 to the server and use it for further calculations

REST API サーバーと examples/7Dimensional_optimization_and_plotting.ipynb の例から始め、特に res.models[-1].sample_y(...) の呼び出しを確認してください。#6 で説明されている pickle 化された結果のアプローチを確認し、訓練済みモデルに対する動的な計算をどのように公開すべきかを特定してください。サーバーがローカルの Python へのアクセスを必要とせずに、要求されたモデル計算を実行できれば完了です。

索引モデルが issue の本文から書いたものです。