Useful code for different Kaggle competitions. Currently covering RSNA-MICCAI Brain Tumor Radiogenomic Classification Kaggle competition.
Project description
Kaggle Recipes
What's New
Aug 27, 2021
-
Released the library on PyPI.
-
Easily create voxel manipulated dataset for RSNA-MICCAI Brain Tumor Classification competition.
-
Extract dicom metadata.
-
Added utilities to log dataframe as tables and files/directory as artifacts.
-
Added utiities to log basic W&B charts (line, bar, and scatter).
Kaggle Competitions
Code & Scripts
RSNA-MICCAI Brain Tumor Radiogenomic Classification
- LINK TO NOTEBOOK
Install
pip install kagglerecipes
Sample Datasets
We have also logged smaller subsets of Kaggle commpeition datasets local development and fast prototyping.
RSNA-MICCAI Brain Tumor Radiogenomic Classification
- Download it manually from here.
- Or download it using this code snippet.
import wandb run = wandb.init() artifact = run.use_artifact('wandb_fc/rsna-miccai-brain/sample:v0', type='dataset') artifact_dir = artifact.download()
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file kagglerecipes-0.0.2.tar.gz
.
File metadata
- Download URL: kagglerecipes-0.0.2.tar.gz
- Upload date:
- Size: 14.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.7.1 pkginfo/1.5.0.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c283b0151c468cae79cbc51e437108bb94b3b2612d41871ec183111a2f0d05ae |
|
MD5 | b46ed4a7d7c7b76a64904f625f48103d |
|
BLAKE2b-256 | 5e4e8e28fc9d8cd677b26696821c20a7f4ffd28dbd15ad0995be62efc71cb641 |
File details
Details for the file kagglerecipes-0.0.2-py3-none-any.whl
.
File metadata
- Download URL: kagglerecipes-0.0.2-py3-none-any.whl
- Upload date:
- Size: 13.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.7.1 pkginfo/1.5.0.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2626e1639b54c27179d9701abf40b34e114a7bc4faba85ec63c1946ade36a220 |
|
MD5 | 2e00daced1747ac7c817bd3d0d9dc48d |
|
BLAKE2b-256 | b4a726ebbf3ef32e4f761d02a8926f010dda73787032a524a92a0ca6b4507e66 |