Update README.md and requirementx.txt

Author: cr-xu

README.md

@@ -0,0 +1,57 @@
+# Tutorial on basic neural network concepts
+
+## Getting-Started
+
+You need to install the dependencies before running the notebooks.
+
+### Using conda
+
+If you don't have conda installed already and want to use conda for environment management, you can install the miniconda as [described here](https://docs.conda.io/projects/miniconda/en/latest/miniconda-install.html).
+
+- Create a conda env with `conda create -n nn-tutorial python=3.10`
+- Activate the environment with `conda activate nn-tutorial`
+- Install the required packages via `pip install -r requirements.txt`.
+
+### Using venv only
+
+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
+```
+
+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
+```
+
+Afterwards, you should be able to run the provided notebooks.
+
+## Running the tutorial
+
+After installing the package
+
+You can start the jupyterlab in the terminal, and it will start a browser automatically
+
+```bash
+jupyter lab
+```
+
+Alternatively, you can use supported Editor to run the jupyter notebooks, e.g. with VS Code.
+
+### Jupyter Notebooks
+
+Use `cmd+Enter` to execute one cell block
+
+### Part 1 Neural Network Basics
+
+The first part of the tutorial is in `1-neural_networks.ipynb`.
+
+### Part 2 MNIST Training
+
+The second part of the tutorial is in `2-mnist_training.ipynb`

requirements.txt

@@ -5,3 +5,4 @@ numpy
 scikit-learn
 scikit-optimize
 torch
+torchvision