Spam detection with streamlit

Web app for spam detection built with streamlit.

Setup Environment

Before running the code, you must setup the python environment that's specified within the environment.yml file. To do so, run the following commands within your terminal:

• $ conda env create -f environment.yml
• $ conda activate spam_detection_streamlit

In case you want to remove this environment later on, use the following command:
$ conda remove --name spam_detection_streamlit --all

Model training

The dataset is save in the data folder. The code for model training is contained in the notebook entitled train_model.ipynb. In order to train a spam detection model, you must run this notebook. Once it is done, a spam_classifier.joblib file will be save to the root directory.

Model serving

The code that's necessary to serve the model with streamlit is available in the streamlit_app.py file. In order to launch the streamlit app, run this script with the following command:
$ streamlit run streamlit_app.py