https://github.com/borda/kaggle_sandbox

starting point for Kaggle attempt :]
https://github.com/borda/kaggle_sandbox

kaggle kaggle-competition python sandbox template-project

Last synced: 11 days ago
JSON representation

starting point for Kaggle attempt :]

• Host: GitHub
• URL: https://github.com/borda/kaggle_sandbox
• Owner: Borda
• License: mit
• Created: 2021-01-18T15:22:58.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2024-10-07T18:54:38.000Z (about 1 month ago)
• Last Synced: 2024-10-10T02:25:02.777Z (about 1 month ago)
• Topics: kaggle, kaggle-competition, python, sandbox, template-project
• Language: Python
• Homepage: https://borda.github.io/kaggle_sandbox
• Size: 95.7 KB
• Stars: 17
• Watchers: 4
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Codeowners: .github/CODEOWNERS__

Awesome Lists containing this project

README

        
# Kaggle sandbox

[![CI complete testing](https://github.com/Borda/kaggle_sandbox/actions/workflows/ci_testing.yml/badge.svg?branch=main&event=push)](https://github.com/Borda/kaggle_sandbox/actions/workflows/ci_testing.yml)

[![codecov](https://codecov.io/gh/Borda/kaggle_sandbox/branch/main/graph/badge.svg)](https://codecov.io/gh/Borda/kaggle_sandbox)

[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/Borda/kaggle_sandbox/main.svg)](https://results.pre-commit.ci/latest/github/Borda/kaggle_sandbox/main)

This is a simple template project to Kaggle participation...

### Expected content:

- a core package with functionalities used across scripts and notebooks

- tutorial/experiment notebooks (in _notebook_ folder if needed)

- \[optional\] some functionality testing aka unittests or doctests

### What to write here:

- simple completion description + link

- shortly what task it is to solve

- list/link online sources

- link kernels/submissions

![sample figure](./assets/demo-glances.jpg)

## Showcases

### Some derived projects

- [Multiple image classification](https://github.com/Borda/kaggle_image-classify)

  - [Herbarium 2022](https://www.kaggle.com/competitions/herbarium-2022-fgvc9)

  - [Plant Pathology 2021 - FGVC8](https://www.kaggle.com/c/plant-pathology-2021-fgvc8) as multi-label classification on apple tree leaf

  - [iMet Collection 2021 x AIC - FGVC8](https://www.kaggle.com/c/imet-2021-fgvc8) as multi-label classification on museum objects

  - [Cassava Leaf Disease Classification](https://www.kaggle.com/c/cassava-leaf-disease-classification/overview)

  - etc.

- [Multiple Image segmentation](https://github.com/Borda/kaggle_image-segm)

  - [Tract Image Segmentation](https://www.kaggle.com/competitions/uw-madison-gi-tract-image-segmentation) as semantic 3D segmentation from MRI scans

  - [Cell Instance Segmentation](https://www.kaggle.com/c/sartorius-cell-instance-segmentation) in microscopy images

  - etc.

- [COVID detection](https://borda.github.io/kaggle_COVID-detection) as object detection on CT (DICOM format) scans

- [Brain Tumor 3D](https://borda.github.io/kaggle_brain-tumor-3D) as image classification on MRI scans

### Author's writing

- [Best Practices to Rank on Kaggle Competition with PyTorch Lightning and Grid.ai Spot Instances](https://devblog.pytorchlightning.ai/best-practices-to-rank-on-kaggle-competition-with-pytorch-lightning-and-grid-ai-spot-instances-54aa5248aa8e)

- [Practical Lighting Tips to Rank on Kaggle Image Challenges](https://devblog.pytorchlightning.ai/practical-tips-to-rank-on-kaggle-image-challenges-with-lightning-242e2e533429)

- [Tackling the Kaggle COVID Detection Challenge with Lightning Flash and IceVision](https://medium.com/codex/tackle-covid-detection-with-lightning-flash-and-icevision-3f66f28c24ac)

- [Simple 3D MRI classification ranked bronze on Kaggle](https://towardsdatascience.com/simple-3d-mri-classification-ranked-bronze-on-kaggle-87edfdef018a)

- [Tabular Classification and Regression Made Easy with Lightning Flash](https://pub.towardsai.net/tabular-classification-and-regression-made-easy-with-lightning-flash-d33bea76a645)

- [Easy Kaggle Offline Submission With Chaining Kernel Notebooks](https://towardsdatascience.com/easy-kaggle-offline-submission-with-chaining-kernels-30bba5ea5c4d)

- [Kaggle hacking: Validate a simple hypothesis against a hidden dataset](https://towardsdatascience.com/kaggle-hacking-validate-a-simple-hypothesis-against-a-hidden-dataset-4cf02bb16510)