This is the folder for PetFinder.my Adoption Prediction competition, team "BaMoOaAl"

Team Components:

• https://www.kaggle.com/alessandrosolbiati, SolbiatiAlessandro
• https://www.kaggle.com/oanaflorescu, flores-o

We will follow along Standford CS231-n assignments and implement them here on the competition.

ROADMAP:

Models:

• KNN: best validation score: 0.20 + 0.14 public LB score: 0.279 BIMODEL
• NB: best validation score: 0.10249 public LB score: 0.172
• implement SVM: best validation score: public LB score:
• implement NN (ResNet transfer learning)
• LGBM: best validation score: 0.17435 public LB score: 0.278
• CATBOOST: best validation score: 0.20133 public LB score: 0.349

Framework:

• write standard PredictiveModel
• write test
• write benchmark/execution scripts ( we are using notebooks )
• write docs with model performance and insight
• add code coverage

Exploratory Data Analysis + Feature Engineering

• Adoption Speed
• Name
• Age
• Breed
• Color
• Size
• Country
• Images