for those who are learning ML with old books
- build docker image
$ ./build.sh
- run jupyter notebook
$ ./run.sh
there are 3 sub-directories mounted to docker for convenience. each of them is intended for..
- work : repository for .ipynb files
- tf_logs : data exported from tensorflow (e.g. models, logs, etc.)
- data : sample data for training of your own
- python2
- Tensorflow (1.15 non-GPU)
- pandas
- numpy
- matplotlib
- scikit-learn