Neural-Network-Visualizer-Web-App

Web based visualization of neural network prediction using keras and streamlit.

Initial setup

1. Clone the repository: git clone https://github.com/nvanandsah/Neural-Network-Visualizer-Web-App.git
2. Install virtualenv: (sudo) pip install virtualenv (sudo if required).
3. cd <repository-path>
4. virtualenv venv
5. Activate virtual environment:
   For mac and linux: source venv/bin/activate.
   For windows: source venv/bin/activate.
6. Install the python libraries: pip install -r requirements.txt

Running the program

1. Train the model using python train_model.py.
2. Start the flask server using python ml_server.py.
3. While the flask server is running, in a new terminal activate the virtual environment and run streamlit server using streamlit run app.py

To start working

1. Activate virtual environment: source venv/bin/activate
2. git checkout master
3. git pull
4. Create a new working branch: git checkout -tb <new-working-branch-name>.

To push your changes-

1. Make sure you are in the new branch you created. You can check the current working branch using git branch.
2. git add .
3. git commit -m "<commit-message>"
4. git push origin <branch-name>
5. Create a pull request.

If you ever install a new python library, make sure to run this command

pip freeze > requirements.txt