Serving Machine Learning Models through REST APIs using Flask in Python

Key	Value
Course Codes	BBT 4206
Course Names	BBT 4206: Business Intelligence II (Week 4-6 of 13)
Semester	August to November 2025
Lecturer	Allan Omondi
Contact	aomondi@strathmore.edu
Note	The lecture contains both theory and practice. This notebook forms part of the practice. It is intended for educational purposes only. Recommended citation: BibTex

Repository Structure

.
├── Docker-Compose.yaml
├── Dockerfile.flask-gunicorn-app
├── Dockerfile.nginx
├── LICENSE
├── Procfile
├── README.md
├── RecommendedCitation.bib
├── api.py
├── app_server_reverse_proxy_server_setup.md
├── container-volumes
│   └── nginx
│       ├── certs
│       │   ├── selfsigned.crt
│       │   └── selfsigned.key
│       └── nginx.conf
├── frontend
│   ├── Proxies.png
│   ├── RequestFlow.png
│   ├── api_consumer.py
│   ├── api_test_DT_classifier.html
│   ├── api_test_DT_regressor.html
│   └── index.html
├── huggingface-spaces-using-gradio
│   ├── app.py
│   └── requirements.txt
├── lab_submission_instructions.md
├── model
│   ├── decisiontree_classifier_baseline.pkl
│   ├── decisiontree_regressor_optimum.pkl
│   ├── knn_classifier_optimum.pkl
│   ├── label_encoders_1b.pkl
│   ├── label_encoders_2.pkl
│   ├── label_encoders_4.pkl
│   ├── label_encoders_5.pkl
│   ├── naive_Bayes_classifier_optimum.pkl
│   ├── onehot_encoder_3.pkl
│   ├── random_forest_classifier_optimum.pkl
│   ├── scaler_4.pkl
│   ├── scaler_5.pkl
│   └── support_vector_classifier_optimum.pkl
├── publicly_serving_the_model_for_validation_by_domain_experts.md
├── requirements.txt
├── rules
├── runtime.txt
├── setup_instructions.md
└── streamlit-sharing-using-streamlit
    ├── app.py
    └── requirements.txt

9 directories, 40 files

Setup Instructions

• Setup Instructions

Lab Manual

Refer to the files below for more details:

1. api_consumer.py
2. api.py
3. api_test_DT_classifier.html
4. api_test_DT_regressor.html
5. Reverse Proxy Server and Application Server Setup
6. Publicly Serving the Model for Validation by Domain Experts

Lab Submission Instructions

• Lab Submission Instructions