.github/workflows --> ci/cd pipeline
infra --> for creating a kube cluster IAAC
app/api_pred.py --> model inferencing api
k8s --> kubernetes manifests
Dockerfile --> creating docker image
preprocess_data.py --> preprocessing enron raw data
requirements.txt --> required python packages
spam_ham_bert.ipynb --> finetuning or training the spam-ham dataset and evaluating and saving the model
precision recall f1-score support
0 0.84 0.93 0.88 2858
1 0.96 0.91 0.93 5651
accuracy 0.91 8509
macro avg 0.90 0.92 0.91 8509 weighted avg 0.92 0.91 0.92 8509