adding theory to notebook + slide capabilities

Author: ansantam

README.md

@@ -1,16 +1,13 @@
 # Tutorial on introduction to Bayesian optimization
-
 [![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
 
 - [Download the repository](#download-the-repository)
 - [Getting started](#getting-started)
 - [Running the tutorial](#running-the-tutorial)
-- [Citing the tutorial](#citing-the-tutorial)
 
 ## Material for this tutorial
-
 - The theoretical lecture can be found here
-- The tutorial in slide form can be found [here](https://machine-learning-tutorial.github.io/bayesian-optimization)
+- The tutorial in slide form is here
 
 ## Download the repository
 
@@ -23,14 +20,14 @@ To check if you have it installed, open your terminal and type:
 git --version
 ```
 
-#### Git installation in mac
+#### Git installation in MacOS
 
 ``` bash
 brew update
 brew install git
 ```
 
-#### Git installation in linux
+#### Git installation in Linux
 
 In Ubuntu/Debian
 
@@ -47,7 +44,7 @@ sudo yum install git
 Once you have Git installed open your terminal, go to your desired directory, and type:
 
 ``` bash
-git clone https://github.com/machine-learning-tutorial/bayesian-optimization.git
+git clone https://github.com/machine-learning-tutorial/bayesian-optimization
 cd bayesian-optimization
 ```
 
@@ -72,6 +69,14 @@ If you don't have conda installed already and want to use conda for environment
 - Create a conda env with `conda create -n bo-tutorial python=3.10`
 - Activate the environment with `conda activate bo-tutorial`
 - Install the required packages via `pip install -r requirements.txt`.
+- Run the following commands:
+
+```bash
+python -m jupyter contrib nbextension install --user
+python -m jupyter nbextension enable varInspector/main
+```
+
+- **After the tutorial** you can remove your environment with `conda remove -n bo-tutorial --all`
 
 ### Using venv only
 
@@ -80,15 +85,17 @@ If you do not have conda installed:
 Alternatively, you can create the virtual env with `venv` in the standard library
 
 ```bash
-python -m venv nn-tutorial
+python -m venv bo-tutorial
 ```
 
-and activate the env with `source <venv>/bin/activate` (bash) or `C:> <venv>/Scripts/activate.bat` (Windows)
+and activate the env with $ source <venv>/bin/activate (bash) or C:> <venv>/Scripts/activate.bat (Windows)
 
 Then, install the packages with pip within the activated environment
 
 ```bash
 python -m pip install -r requirements.txt
+python -m jupyter contrib nbextension install --user
+python -m jupyter nbextension enable varInspector/main
 ```
 
 Afterwards, you should be able to run the provided notebooks.
@@ -97,22 +104,21 @@ Afterwards, you should be able to run the provided notebooks.
 
 After installing the package
 
-You can start the jupyterlab in the terminal, and it will start a browser automatically
+You can start the jupyter notebook in the terminal, and it will start a browser automatically
 
 ```bash
-jupyter lab
+python -m jupyter notebook
 ```
 
 Alternatively, you can use supported Editor to run the jupyter notebooks, e.g. with VS Code.
 
-## Citing the tutorial
+### Jupyter Notebooks
 
-This tutorial is published in [Zenodo](https://zenodo.org/) with a DOI for each code release.
+Use `cmd+Enter` to execute one cell block
 
+## Citing the tutorial
+This tutorial is registered [Zenodo](https://zenodo.org/), which means that there is a DOI for each code release. 
 Please use this DOI when citing this code:
 
 ## Disclaimer
-
 The content of this repository was developed by the [AI4Accelerators team](https://www.ibpt.kit.edu/AI4Accelerators.php) at the [Institute of Beam Physics and Technology (IBPT)](https://www.ibpt.kit.edu/), [Karlsruhe Institute of Technology](https://www.kit.edu/english/).
-
-The ARES environment was adapted from the original version, developed by [Jan Kaiser](https://github.com/jank324).