- Predictive modeling Notebooks for Kaggle competition
- Tools
- Language: Python3.7
- Modeling Framework: Scikit-Learn, PyTorch
- Hyper-parameter Optimization Tool: Ray Tune
- Working Environment: Colab Notebook
Competition / Data | Problem Type | Code |
---|---|---|
Titanic Survival Prediction | Binary Classification | Notebook(kor) |
House Price Prediction | Regression | Notebook(kor) |
Forest Cover Type Prediction | Multi-class Classification | Notebook(kor) |
Bike Sharing Demand | Multi-output Regression | Notebook(kor) |
Prudential Life Insurance Assessment | Ordinal Classification | Notebook(kor) |
Competition / Data | Problem Type | Model | Code |
---|---|---|---|
NASA Turbofan Jet Engine | Multivariate Time-Series Scalar Forecasting (Remaining Useful Life Prediction) |
LSTM | Notebook |
Pump Sensor | Multivariate Time-Series Anomaly Detection | LSTM_AutoEncoder | Notebook |
Competition / Data | Problem Type | Model | Code |
---|---|---|---|
Dog Breed Identification | Classification | ResNet34(Pretrained) ResNet18 NiN |
Notebook Notebook Notebook |
Generative Dog Images | Generation | DCGAN | Notebook |
I’m Something of a Painter Myself | Style Transfer | Neural Style Transfer | Notebook |
PASCAL VOC 2012 | Semantic Segmentation | FCN_ResNet18 | Notebook |