Project Instructions

This repo contains the instructions for a machine learning project.

Do Not Forget to mention the Python Version being used and complete the requirements.txt fil

Project Organization

├── README.md          <- The top-level README for describing highlights for using this ML project.
│
├── notebooks          <- Jupyter notebooks. Naming convention should snake case.
│
├── reports            
│   └── figures        <- Generated graphics and figures to be used in reporting
│   └── README.md      <- Youtube Video Link
│   └── final_project_report <- final report .pdf format and supporting files
│   └── presentation   <-  final power point presentation 
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├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── src                <- Source code for use in this project.
   ├── __init__.py    <- Makes src a Python module
   ├── data
   │   ├── processed      <- The final, canonical data sets for modeling.
   │   └── raw            <- The original, immutable data dump.
   │
   ├── preprocessing_data           <- Scripts to download or generate data and pre-process the data
   │   └── pre-processing.py
   │
   ├── feature_engineering       <- Scripts to turn raw data into features for modeling
   │   └── build_features.py
   │
   ├── models         <- Scripts to train models and then use trained models to make
   │   │                 predictions
   │   ├── predict_model.py
   │   └── train_model.py
   │
   └── visualization  <- Scripts to create exploratory and results oriented visualizations
   │   └── visualize.py  
   │
   └── main.py  <- main script to run all the models and call appropriate functions
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   ├── LICENSE  <- LICENSE terms to be included for the use of the source code distribution