[docs] Small fixes in documentation (#1380)

* fixed PR #1371

* fixed PR #1370

docs/source/contents.rst

@@ -39,31 +39,6 @@ NeuralProphet changes the way time series modelling and forecasting is done:
     >>> forecast = m.predict(your_df)
     >>> m.plot(forecast)
 
-
-Installing
-----------
-
-NeuralProphet can be installed with `pip <https://pypi.org/project/neuralprophet/>`_:
-
-.. code-block:: bash
-
-    $ pip install neuralprophet
-
-If you plan to use the package in a Jupyter notebook, we recommend to install the 'live' version:
-
-.. code-block:: bash
-
-    $ pip install neuralprophet[live]
-
-Alternatively, you can get the most up to date version by cloning directly from `GitHub <https://github.com/ourownstory/neural_prophet>`_:
-
-.. code-block:: bash
-
-    $ git clone https://github.com/ourownstory/neural_prophet.git
-    $ cd neural_prophet
-    $ pip install .
-
-
 .. toctree::
     :hidden:
     :maxdepth: 1

docs/source/how-to-guides/index.rst

@@ -13,9 +13,8 @@ Feature guides
     Global Local Modelling<feature-guides/global_local_modeling>
     Live Plotting during Training<feature-guides/Live_plot_during_training>
     Network Architecture Visualization<feature-guides/network_architecture_visualization>
-    Prophet to TorchProphet<feature-guides/prophet_to_torch_prophet>
+
     Plotting<feature-guides/plotly>
-    Migration from Prophet<feature-guides/Migration_from_Prophet>
     Multiplicative Seasonality<feature-guides/season_multiplicative_air_travel>
     Sparse Autoregression<feature-guides/sparse_autoregression_yosemite_temps>
     Subdaily data<feature-guides/sub_daily_data_yosemite_temps>
@@ -42,4 +41,5 @@ Migrate From Prophet
 .. toctree::
    :maxdepth: 1
 
-   Changes from prophet<changes-from-prophet>
+   Migration from Prophet<feature-guides/Migration_from_Prophet>
+   Prophet to TorchProphet<feature-guides/prophet_to_torch_prophet>

docs/source/quickstart.ipynb

@@ -9,9 +9,19 @@
     "This page contains details of how you can build a simple model using NeuralProphet with minimal features.\n",
     "\n",
     "## Install\n",
-    "After downloading the code repository (via `git clone`), change to the repository directory (`cd neural_prophet`) and install neuralprophet as python package with `pip install .`\n",
+    "NeuralProphet can be installed with [pip](https://pypi.org/project/neuralprophet/):\n",
     "\n",
-    "Note: If you plan to use the package in a Jupyter notebook, it is recommended to install the `live` package version with `pip install .[live]`. This will allow you to enable `progress='plot'` in the train function to get a live plot of train (and validation) loss.\n",
+    "    $ pip install neuralprophet\n",
+    "\n",
+    "If you plan to use the package in a Jupyter notebook, we recommend to install the 'live' version. This will allow you to enable `progress='plot'` in the train function to get a live plot of train (and validation) loss.\n",
+    "\n",
+    "    $ pip install neuralprophet[live]\n",
+    "\n",
+    "Alternatively, you can get the most up to date version by cloning directly from `GitHub <https://github.com/ourownstory/neural_prophet>`_:\n",
+    "\n",
+    "    $ git clone https://github.com/ourownstory/neural_prophet.git\n",
+    "    $ cd neural_prophet\n",
+    "    $ pip install .\n",
     "\n",
     "### Import\n",
     "Now you can use NeuralProphet in your code:"
@@ -496,7 +506,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.16"
+   "version": "3.9.17"
   },
   "orig_nbformat": 4
  },