Giter Club home page Giter Club logo

ai_precourse's Introduction

Notebook Project Template

Overview

This project template is designed for data science and analytics workflows using Jupyter Notebooks. It provides a structured and standardized way to organize code, data, and outputs for efficient and reproducible research.

Structure

The template is organized into the following directories:

  • data/: Contains raw and processed data.
    • raw/: Stores the original, unaltered data.
    • processed/: Holds data that has been cleaned, transformed, or otherwise processed.
  • notebooks/: Contains Jupyter notebooks (.ipynb files) used for analysis and data processing.
  • scripts/: For standalone Python scripts, often used for more complex or reusable code.
  • utils/: Includes utility functions and helper scripts.
  • outputs/: Stores the results and products of analyses.
    • figures/: For plots, charts, and other visualizations.
    • data/: Final or exported data sets, ready for sharing or publishing.
    • logs/: Log files for tracking and debugging.
    • models/: Trained machine learning model files.
    • summaries/: Textual output such as reports and summaries.
  • env/: Virtual environment directory (not tracked by version control).

Getting Started

  1. Set Up Environment:

    • Create a virtual environment: python -m venv env
    • Activate the environment:
      • Windows: .\env\Scripts\activate
      • Unix/macOS: source env/bin/activate
    • Install required packages: pip install -r requirements.txt
  2. Working with Notebooks:

    • Jupyter notebooks are located in the notebooks/ directory.
    • Start JupyterLab with jupyter lab and open notebooks from the interface.
  3. Using the Data Directory:

    • Place your raw data in data/raw/.
    • Save processed data in data/processed/.
  4. Scripts and Utilities:

    • Store reusable scripts in scripts/.
    • Place utility functions in utils/.
  5. Saving Outputs:

    • Save figures and plots in outputs/figures/.
    • Export final data sets to outputs/data/.
  6. Logging:

    • Generate and store log files in outputs/logs/.

Best Practices

  • Keep raw data immutable to maintain data integrity.
  • Document each step in your Jupyter notebooks for clarity and reproducibility.
  • Write modular and reusable code in scripts and utility functions.
  • Regularly commit changes to version control.

This template provides a foundational structure to kickstart your notebook-based projects, ensuring that your work remains organized and adheres to best practices in data science.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.