Anisha-20110-pset2

assignment 2 ML-Ops

Project Organization

├── Artifacts               <- Contains genrated trained model's .pkl files
├── Makefile                <- Makefile with commands like `make data` or `make train`
├── README.md               <- The top-level README for developers using this project.
├── data
│   ├── external            <- Data from third party sources.
│   ├── processed           <- The final, canonical data sets for modeling.
│   └── raw                 <- The original, immutable data dump.
├── models                  <- Trained and serialized models, model predictions, or model summaries
│
├── requirements.txt        <- The requirements file for reproducing the analysis environment, e.g.
│                             generated with `pip freeze > requirements.txt`
├── setup.py                <- makes project pip installable (pip install -e .) so src can be imported
├── src                     <- Source code for use in this project.
│   ├── __init__.py         <- Makes src a Python module
│   │
│   ├── data                <- Scripts to download or generate data
│   │   └── load_and_process_data.py
│   │
│   ├── models              <- Scripts to train models and then use trained models to make
│       │                       predictions
│       └── train_model.py  <- To train model: python3 src/models/train_model.py
│   
│
└── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io

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Project based on the cookiecutter data science project template.

Inorder to run the model, you will need to set your mlflow and dagshub credentials

dvc remote modify origin --local auth basic
dvc remote modify origin --local user <DAGSHUB_ID>
dvc remote modify origin --local password <DAGSHUB_TOKEN>

export MLFLOW_TRACKING_USERNAME=<DAGSHUB_ID>
export MLFLOW_TRACKING_PASSWORD=<DAGSHUB_TOKEN>

Links:

DagsHub: https://dagshub.com/anibhush/Anisha-20110-pset2
https://dagshub.com/anibhush/Anisha-20110-pset2/experiments/#/

Data Flow Pipeline:

ML Flow: