본 캐글 스터디는 '커널 커리큘럼'을 참고합니다.
(커널 커리큘럼 작성자 이유한님 - https://www.kaggle.com/youhanlee)
스터디원은 총 6명으로, 각자 그날의 과제에 대해 레퍼지토리에 업로드를 목표로 하고 있습니다. (2021/01/18 시작)
- 김현하
- 시온
- 유재성
- 이동훈
- 이희주
- H00
1st level. Titanic competition (https://https://www.kaggle.com/c/titanic)
- 1st kernel
(https://kaggle-kr.tistory.com/17?category=868316,(2021-01-18)
https://kaggle-kr.tistory.com/18?category=868316)(2021-01-19) - 2nd kernel (https://www.kaggle.com/ash316/eda-to-prediction-dietanic)
- 3rd kernel (https://www.kaggle.com/yassineghouzam/titanic-top-4-with-ensemble-modeling)
- 4th kernel (https://www.kaggle.com/arthurtok/introduction-to-ensembling-stacking-in-python)
2nd level. Porto (https://www.kaggle.com/c/porto-segurosafe-driver-prediction)
- 1st kernel (https://www.kaggle.com/bertcarremans/data-preparation-exploration)
- 2nd kernel (https://www.kaggle.com/arthurtok/interactive-porto-insights-a-plot-ly-tutorial)
- 3rd kernel (https://www.kaggle.com/aharless/xgboost-cv-lb-284)
- 4th kernel (https://www.kaggle.com/gpreda/porto-seguro-exploratory-analysis-and-prediction)
3rd level. Home credit competition (https://www.kaggle.com/c/home-credit-default-risk)
- 1st kernel (https://www.kaggle.com/willkoehrsen/start-here-a-gentle-introduction)
- 2nd kernel (https://www.kaggle.com/willkoehrsen/introduction-to-manual-feature-engineering)
- 3rd kernel (https://www.kaggle.com/eliotbarr/stacking-test-sklearn-xgboost-catboost-lightgbm)
- 4th kernel (https://www.kaggle.com/jsaguiar/lightgbm-7th-place-solution)
1st level. Costa-rican competition (https://www.kaggle.com/c/costa-rican-household-povertyprediction)
- 1st kernel (https://www.kaggle.com/willkoehrsen/a-complete-introduction-and-walkthrough)
- 2nd kernel (https://www.kaggle.com/youhanlee/3250feats-532-feats-using-shap-lb-0-436)
- 3rd kernel (https://www.kaggle.com/skooch/xgboost)
1st level. Statoil competition (https://www.kaggle.com/c/statoiliceberg-classifier-challenge)
- 1st kernel (https://www.kaggle.com/devm2024/keras-model-for-beginners-0-210-on-lb-eda-r-d)
- 2nd kernel (https://www.kaggle.com/devm2024/transfer-learning-with-vgg-16-cnn-aug-lb-0-1712)
- 3rd kernel (https://www.kaggle.com/submarineering/submarineering-even-better-public-score-until-now)
- 4th kernel (https://www.kaggle.com/wvadim/keras-tf-lb-0-18)
1st level. Fruits 360 (https://www.kaggle.com/uciml/mushroom-classification)
2nd level. Fashion MNIST (https://www.kaggle.com/zalandoresearch/fashionmnist)
- 1st kernel (https://www.kaggle.com/shivamb/how-autoencoders-work-intro-and-usecases)
- 2nd kernel (https://www.kaggle.com/bugraokcu/cnn-with-keras)
1st level. Tensorflow competition (https://www.kaggle.com/c/tensorflowspeech-recognition-challenge)
- 1st kernel (https://www.kaggle.com/davids1992/speech-representation-and-data-exploration)
- 2nd kernel (https://www.kaggle.com/alphasis/light-weight-cnn-lb-0-74)
- 3rd kernel (https://www.kaggle.com/kcs93023/tf-speech-recognition-by-cnn)
- 4th kernel (https://www.kaggle.com/ivallesp/wavception-v1-a-1-d-inception-approach-lb-0-76)
1st level. New-York taxi competition (https://www.kaggle.com/c/nyc-taxitrip-duration)
- 1st kernel (https://www.kaggle.com/gaborfodor/from-eda-to-the-top-lb-0-367)
- 2nd kernel (https://www.kaggle.com/drgilermo/dynamics-of-new-york-city-animation)
- 3rd kernel (https://www.kaggle.com/aiswaryaramachandran/eda-baseline-model-0-40-rmse)
- 4th kernel (https://www.kaggle.com/danijelk/beat-the-benchmark)
1st level. Zillow competition (https://www.kaggle.com/c/zillow-prize-1)
- 1st kernel (https://www.kaggle.com/sudalairajkumar/simple-exploration-notebook-zillow-prize)
- 2nd kernel (https://www.kaggle.com/anokas/simple-xgboost-starter-0-0655)
- 3rd kernel (https://www.kaggle.com/viveksrinivasan/zillow-eda-on-missing-values-multicollinearity)
- 4th kernel (https://www.kaggle.com/aharless/xgboost-lightgbm-and-ols-and-nn)
1st level. Data bowl 2018 (https://www.kaggle.com/c/datascience-bowl-2018)
- 1st kernel (https://www.kaggle.com/stkbailey/teaching-notebook-for-total-imaging-newbies)
- 2nd kernel (https://www.kaggle.com/keegil/keras-u-net-starter-lb-0-277)
- 3rd kernel (https://www.kaggle.com/kmader/nuclei-overview-to-submission)
1st level. Spooky competition (https://www.kaggle.com/c/spookyauthor-identification)
- 1st kernel (https://www.kaggle.com/arthurtok/spooky-nlp-and-topic-modelling-tutorial)
- 2nd kernel (https://www.kaggle.com/abhishek/approaching-almost-any-nlp-problem-on-kaggle)
- 3rd kernel (https://www.kaggle.com/sudalairajkumar/simple-feature-engg-notebook-spooky-author)
2nd level. Mercari (https://www.kaggle.com/c/mercari-price-suggestion-challenge)
- 1st kernel (https://www.kaggle.com/thykhuely/mercari-interactive-eda-topic-modelling)
- 2nd kernel (https://www.kaggle.com/knowledgegrappler/a-simple-nn-solution-with-keras-0-48611-pl)
- 3rd kernel (https://www.kaggle.com/rumbok/ridge-lb-0-41944)
- 4th kernel (https://www.kaggle.com/peterhurford/lgb-and-fm-18th-place-0-40604)
3rd level. Toxic competition (https://www.kaggle.com/c/jigsawtoxic-comment-classificationchallenge)
- 1st kernel (https://www.kaggle.com/sbongo/for-beginners-tackling-toxic-using-keras)
- 2nd kernel (https://www.kaggle.com/jagangupta/stop-the-s-toxic-comments-eda)
- 3rd kernel (https://www.kaggle.com/tunguz/logistic-regression-with-words-and-char-n-grams)
- 4th kernel (https://www.kaggle.com/rhodiumbeng/classifying-multi-label-comments-0-9741-lb)
1st level. Credit card (https://www.kaggle.com/mlg-ulb/creditcardfraud)
- 1st kernel (https://www.kaggle.com/joparga3/in-depth-skewed-data-classif-93-recall-acc-now)
- 2nd kernel (https://www.kaggle.com/pavansanagapati/anomaly-detection-credit-card-fraud-analysis)
- 3rd kernel (https://www.kaggle.com/matheusfacure/semi-supervised-anomaly-detection-survey)