We are making a stock chart analysis web service using Django and Bootstrap. We didn't link our page using docker or something else so if you want to check our page, you must download.
To begin using this template, choose one of the following options to get started:
After installation, Create a virtual environment to install the things need to do. Stock DB is not uploaded so check dropbox to get db.sqlite3. And run pip install -r requirements.txt and run python manage.py runserver. Then you can see that our page is working.
# create virtual environment & activate
# Windows
python -m venv venv
venv\Scripts\activate
# Mac
virtualenv venv --python=python3.8
source venv/bin/activate
# install PyTorch
https://pytorch.org/get-started/locally/
# install packages
pip install -r requirements.txt
# download stock db file on dropbox/team1
https://www.dropbox.com/home/TEAM%201
# run web server
python manage.py runserver
# access the page
http://127.0.0.1:8000
informations about our team and service from the page / make your own account / login & logout / bookmark a stock item / check predicted pattern /
refine page design / replace with a better model
Please access the following url to see our website deployed: Fastock
Our model was trained using a library called Fastai. It is able to classify 8 different stock patterns, and has an accuracy of 95.43% To see the model, please visit the following link: Fastock Machine Learning Model