Metadata-Version: 2.1
Name: otto-ml
Version: 0.1.30
Summary: Otto is a simple Boilerplate for Machine Learning projects integrated with MLflow tools
Home-page: https://github.com/carlos-rodrigo/otto-ml
Author: Carlos Rodrigo
Author-email: hi@carlosrodrigo.me
License: UNKNOWN
Description: # OTTO
        Otto is a simple Boilerplate for Machine Learning projects integrated with MLflow that creates a basic directory structure to organize your code and data.
        Otto is strongly based on [Cookiecutter](https://drivendata.github.io/cookiecutter-data-science/), if you need something more complete is a good desition to visit they repo. 
        
        ```
        ├── MLproject
        ├── README.md
        ├── Dockerfile
        ├── build_image.sh
        ├── .gitignore
        ├── data
        │   ├── processed/
        │   └── raw/
        ├── notebooks/
        ├── src/
        │   ├── data/
        │   │   └── __init__.py
        │   │   └── data_preparation.py
        │   ├── features/
        │   │   └── __init__.py
        │   ├── models/
        │   │   └── __init__.py
        │   │   └── model.py
        │   ├── train.py
        │   ├── settings.py
        │   └── __init__.py
        └── tests/
        ```
        
        ## Usage
        
        Simple install otto using pip as follows
        
        `pip install otto-ml`
        
        and use otto
        
        `otto --name new-project`
        
        or simple use it with out params and let otto guides you 😉
        
        `otto`
        
        and that's it, Now you can jump to code your model! 
        
        ## Ok, but... what this solve?
        
        That is a pretty good question. The first attempt is to simplify the startup of a new machine learning project generating most, not machine-learning related code. Like the configuration of the docker image via `Dockerfile` or the `MLProject` setup and the connection with the Mlflow tracking server if you have set up one using ENV variables. 
        
        But to make it cristal water, let show how it will be a standard use of the `otto` package. 
        
        ### The Titanic Competition Example
        
        ... In development ...
        
        
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Provides-Extra: extras
