Emakia, Machine Learning Project

Machine Learning Project Structure

Set up the config.py with your name

Project Directory Structure

├── Machine Learning Project Structure <- Project Main Directory
|   |── Apple development
|   |── Google Cloud Server Development
|   |   ├── Text Classifier Training
|   |   |   ├── Notebook <- All the ipython notebooks used for EDA, visualization and verification of concept (POC).
|   |   |   ├── Node.js
|   |   |   ├── Validation
|   |   |   |   ├── evaluate_model_01.py <- Different Matries used to validate the model
|   |   |   |   ├──  evaluate_model_02.py <- Different Matries used to validate the model
│   ├── data <- data in different format
|   |   ├── external <- data from third party source
|   |   ├── interim <- Intermediate data that has been transformed
|   |   ├── processed <- The final, canonical data sets for modeling
|   |   ├── raw <- The original, immutable data dump
│   ├── .gitignore <- tells Git which files to ignore when committing your project to the GitHub repository
│   ├── .env <- used to hide the confidential data like AWS Screte Key, AWS  Access Key, S3 Bucket Name etc...
│   ├── README.md <- The top-level README for developers using this project

**Note**: The data folder and .env file won’t appear in github. It will be in your local folder. This is not pushed to githhub as it will be in the ignore list (.gitignore file). If you want to checkin that also, just comment out in .gitignore file and add the data folder to github.

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