diff --git a/README.md b/README.md
index bb2c279..2f9a469 100644
--- a/README.md
+++ b/README.md
@@ -1,30 +1,14 @@
 # Siamese Neural Network for Keras
 
-This project provides a lightweight, easy to use and flexible siamese neural network module for use with the Keras 
+This project provides a lightweight siamese neural network module for use with the Keras 
 framework. 
 
-Siamese neural networks are used to generate embeddings that describe inter and extra class relationships. 
-This makes Siamese Networks like many other similarity learning algorithms suitable as a pre-training step for many 
-classification problems.
+The neural network compares two images and returns their similarity in a 0-1 float value.
+The datasets used are the fruit-360 dataset, COCO 2014 and 2017 as well as some ImageNet data.
 
-An example of the siamese network module being used to produce a noteworthy 99.85% validation performance on the MNIST 
-dataset with no data augmentation and minimal modification from the Keras example is provided.
+# Installation
 
-## Installation
-
-Create and activate a virtual environment for the project.
-```sh
-$ virtualenv env
-$ source env/bin/activate
-```
-
-To install the module directly from GitHub:
-```
-$ pip install git+https://github.com/aspamers/siamese
-```
-
-The module will install keras and numpy but no back-end (like tensorflow). This is deliberate since it leaves the module 
-decoupled from any back-end and gives you a chance to install whatever backend you prefer. 
+- tensorflow
 
 To install tensorflow:
 ```
@@ -36,19 +20,7 @@ To install tensorflow with gpu support:
 $ pip install tensorflow-gpu
 ```
 
-## To run examples
-
-With the activated virtual environment with the installed python package run the following commands.
-
-To run the mnist baseline example:
-```
-$ python mnist_example.py
-```
-
-To run the mnist siamese pretrained example:
-```
-$ python mnist_siamese_example.py
-```
+- If you use tensorflow-gpu, you'll have to install Cuda and CuDNN.
 
 ## Usage
 For detailed usage examples please refer to the examples and unit test modules. If the instructions are not sufficient 
@@ -114,35 +86,6 @@ siamese_network.fit(x_train, y_train,
                     epochs=epochs)
 ```
 
-## Development Environment
-Create and activate a test virtual environment for the project.
-```sh
-$ virtualenv env
-$ source env/bin/activate
-```
-
-Install requirements
-```sh
-$ pip install -r requirements.txt
-```
-
-Install the backend of your choice.
-```
-$ pip install tensorflow
-```
-
-Run tests
-```sh
-$ pytest tests/test_siamese.py
-```
-
-## Development container
-To set up the vscode development container follow the instructions at the link provided:
-https://github.com/aspamers/vscode-devcontainer
-
-You will also need to install the nvidia docker gpu passthrough layer:
-https://github.com/NVIDIA/nvidia-docker
-
 ## requirements
 
 keras==2.2.4