• Description: Final project for Le Wagon Tokyo Bootcamp, for this project we developed 2 deep learning models using Tensorflow Keras to analize the listing of a product in Amazon USA marketplace to evaluate the quality of the SEO (Search Engine Optimization) for a new product in the category of Cellphones and Accessories, taking as features in the first place Text that is analized with a RNN model and images throught a CNN model, in both cases the output we look to predict is the product selling ranking that was divided in 10 categories wich both models classify the Text features and Image features.

• Backend :

  • Tensorflow Keras
  • Fast API
  • Uvicorn
  • Docker
  • GCP

• Frontend:

  • Streamlit
  • Heroku

• Data Source: https://nijianmo.github.io/amazon/index.html

• Authors:

  • Elizabeth Kok
  • Nayoung Kim
  • Cristobal Cepeda

Deep SEO Heroku app

The initial setup.

Create virtualenv and install the project:

sudo apt-get install virtualenv python-pip python-dev
deactivate; virtualenv ~/venv ; source ~/venv/bin/activate ;\
    pip install pip -U; pip install -r requirements.txt

Unittest test:

make clean install test

Check for deep_seo in gitlab.com/{group}. If your project is not set please add it:

• Create a new project on gitlab.com/{group}/deep_seo
• Then populate it:

##   e.g. if group is "{group}" and project_name is "deep_seo"
git remote add origin [email protected]:{group}/deep_seo.git
git push -u origin master
git push -u origin --tags

Functionnal test with a script:

cd
mkdir tmp
cd tmp
deep_seo-run

Go to https://github.com/{group}/deep_seo to see the project, manage issues, setup you ssh public key, ...

Create a python3 virtualenv and activate it:

sudo apt-get install virtualenv python-pip python-dev
deactivate; virtualenv -ppython3 ~/venv ; source ~/venv/bin/activate

Clone the project and install it:

git clone [email protected]:{group}/deep_seo.git
cd deep_seo
pip install -r requirements.txt
make clean install test                # install and test

Functionnal test with a script:

cd
mkdir tmp
cd tmp
deep_seo-run