https://github.com/hunkim/kagglezerotoall
Kaggle problem solving
https://github.com/hunkim/kagglezerotoall
Last synced: 3 months ago
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Kaggle problem solving
- Host: GitHub
- URL: https://github.com/hunkim/kagglezerotoall
- Owner: hunkim
- Created: 2017-03-27T05:20:13.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2017-08-14T22:32:03.000Z (almost 9 years ago)
- Last Synced: 2024-11-26T05:51:53.969Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 7.71 MB
- Stars: 168
- Watchers: 21
- Forks: 71
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# KaggleZeroToAll
After knowing basics of machine learning, deep learning, and TensorFlow/Keras, what's the next?
Kaggle provides many interesting problems for machine learning experts.
This repository hosts interesting Kaggle problems and show how to solve these problems using decent deep learning models.
## Kaggle problem directory naming
k0-00-short-title
* Difficulty (k0, k1, ... k9):
- 0: easy
- 5: normal
- 9: very difficult
* k0-XX: 00 serial number
* short-title: title for the Kaggle data
* put `.py`, `.ipynb`, and data files in the directory
- If data files are large, you can create a script. Please check [this](k0-01-titanic/data_download.sh)
## Content of each file
Please see k0-00-template.ipynb
* Kaggle name
* dataset/problem description
* loading data
* model to solve the problem
* results
* future work and exercises
## Dependencies for Kaggle Utils (optional)
```
requests==2.13.0
beautifulsoup4==4.6.0
```
or
```bash
pip install -r requirements.txt
```
## Kaggle Utils (optional)
* `kaggle_download.py`: Kaggle download script
1. Create **kaggle.ini**
- Copy `kaggle.ini.sample` and name it `kaggle.ini`
- Fill out your `username` and `password` in kaggle.ini
2. **Accept the agreement term** in Kaggle website
- Click the download button on the competition main site
3. Find a **competition name**
* Competition name can be found in the URL
* For example, if the url is https://www.kaggle.com/c/digit-recognizer,
then the competition name is **digit-recognizer**
3. In terminal,
```bash
# python kaggle_download.py competition-name --destination path/to/save/dataset
# Example:
$ python kaggle_download.py digit-recognizer --destination k0-01-mnist/input
```
* `kaggle_submit.py`: Kaggle submission script
1. You can also submit your submission
2. In terminal,
```bash
# python kaggle_submit.py competition-name /path/to/submission.csv -m "Submission message"
# Example:
python kaggle_submit.py digit-recognizer k0-01-mnist/submission.csv -m "First Submission"
```
## Tests
```bash
py.test
```
## Contributions
We welcome any contributions including writing issues and sending pull requests.
## References (Thanks to the TF-KR user group)
* https://www.quora.com/What-Kaggle-competitions-should-a-beginner-start-with-1
* http://ndres.me/kaggle-past-solutions/
* http://www.chioka.in/kaggle-competition-solutions/
* http://analyticscosm.com/learning-predictive-analytics-kaggle-competition-solutions/