melio-consulting/indabax-demo

Deep Learning IndabaX South Africa 2022 MLOps Demo # indabax_demo IndabaX Demo 2022 ## Development Requirements - Python3.11.0 - Pip - Poetry (Python Package Manager) ### M.L Model Environment ```sh MODEL_PATH=./ml/model/ MODEL_NAME=model.pkl ``` ### Update `/predict` To update your machine learning model, add your `load` and `method` change here at `predictor.py` ## Installation ```sh python -m venv venv source venv/bin/activate make install ``` ## Runnning Localhost `make run` ## Deploy app `make deploy` ## Running Tests `make test` ## Runnning Easter Egg `make easter` ## Access Swagger Documentation > ## Access Redocs Documentation > ## Project structure Files related to application are in the `app` or `tests` directories. Application parts are: app | | # Fast-API stuff ├── api - web related stuff. │   └── routes - web routes. ├── core - application configuration, startup events, logging. ├── models - pydantic models for this application. ├── services - logic that is not just crud related. ├── main-aws-lambda.py - FastAPI application for AWS Lambda creation and configuration. └── main.py - FastAPI application creation and configuration. | | # ML stuff ├── data - where you persist data locally │   ├── interim - intermediate data that has been transformed. │   ├── processed - the final, canonical data sets for modeling. │   └── raw - the original, immutable data dump. │ ├── notebooks - Jupyter notebooks. Naming convention is a number (for ordering), | ├── ml - modelling source code for use in this project. │   ├── __init__.py - makes ml a Python module │   ├── pipeline.py - scripts to orchestrate the whole pipeline │ │ │   ├── data - scripts to download or generate data │   │   └── make_dataset.py │ │ │   ├── features - scripts to turn raw data into features for modeling │   │   └── build_features.py │ │ │   └── model - scripts to train mod …