use my Docker images

https://hub.docker.com/r/roccqqck/stock-notebook

sudo docker pull roccqqck/stock-notebook
sudo docker run -it -p 8889:8888 roccqqck/stock-notebook \
   jupyter notebook --no-browser --ip=0.0.0.0 --allow-root --NotebookApp.token='password' --notebook-dir='/'

use your remote server Public Static IP, for example http://140.112.254.4:8889 or http://localhost:8889

mount a folder from your host computer, adding -v /HOST/PATH:/DOCKER/PATH

sudo docker run -it -p 8889:8888 -v /home/username/projects:/root/projects \
   roccqqck/stock-notebook \
   jupyter notebook --no-browser --ip=0.0.0.0 --allow-root --NotebookApp.token='password' --notebook-dir='/'

use my conda environment(linux). Download this link (Save link as)

https://github.com/roccqqck/stock_eland/raw/master/stockenv.environment.yml

wget https://github.com/roccqqck/stock_eland/raw/master/stockenv.environment.yml
conda env create -f stockenv.environment.yml
conda activate stockenv

use pip requirements python=3.6 cuda=10.0 cudnn=7.3.1 nvidia-driver>= 410.48

python3.6 -m venv ~/.local/venvs/stockenv
source ~/.local/venvs/stockenv/bin/activate
python3.6 -m pip install -r https://github.com/roccqqck/stock_eland/raw/master/stockenv.requirements.txt

word vector download link, put them in the main path like "cc.zh.300.vec"

https://fasttext.cc/docs/en/crawl-vectors.html https://github.com/lintseju/word_embedding

dataset, put them into "bda2019_dataset" folder

https://drive.google.com/drive/folders/1ZH2wwiYutOX--734fmWqWYJn5_X3zIIA?usp=sharing