Creating a virtual environment in Python using venv is a great way to manage project-specific dependencies and avoid conflicts with system packages.
- make sure if you have init.py in your 'src'
- python3 -m venv ./env_nn_n00b
- source ./env_nn_n00b/bin/activate
- export PYTHONPATH="${PYTHONPATH}:./" - 'Rexecute the next command from your project dir'
- pip3 install -r requirements.txt
Useful plagins:
TODO:
- add different activation functions and derivatives
- add visualisation for the NN
- visualisation and add 3 lists (LOSS, Acuracy for validation dataset and test dataset) matplotlib or streamlit.
- https://developers.arcgis.com/python/guide/faster-rcnn-object-detector/
- https://analyticsindiamag.com/r-cnn-vs-fast-r-cnn-vs-faster-r-cnn-a-comparative-guide/