kaggle-avito-demand-challenge

Kaggle Avito Demand Challenge (top 1% solution)

Other source codes from another teammate (Zhixiang Hua): https://github.com/CortexFoundation/Avito_rank17/tree/master/code

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
+ad period features.ipynb		+ad period features.ipynb
+all cat mean enc + user feat script.ipynb		+all cat mean enc + user feat script.ipynb
+cat interact feat script.ipynb		+cat interact feat script.ipynb
+mean enc feat script.ipynb		+mean enc feat script.ipynb
Active Training.ipynb		Active Training.ipynb
Active experiments- Gen Data.ipynb		Active experiments- Gen Data.ipynb
Active experiments-activation date version.ipynb		Active experiments-activation date version.ipynb
Active experiments.ipynb		Active experiments.ipynb
All Features Training-Sparse (Ridge, LogisticReg, KNN).ipynb		All Features Training-Sparse (Ridge, LogisticReg, KNN).ipynb
All Features Training.ipynb		All Features Training.ipynb
Common Features Engineering High Cardinality Refactored.ipynb		Common Features Engineering High Cardinality Refactored.ipynb
Common Features Engineering.ipynb		Common Features Engineering.ipynb
Complete TF-IDF Generation.ipynb		Complete TF-IDF Generation.ipynb
Counter Vectorizer (Char_WB).ipynb		Counter Vectorizer (Char_WB).ipynb
Feature Test Part 2 (Text).ipynb		Feature Test Part 2 (Text).ipynb
Feature Test Part3 (Dump file for Marcus use).ipynb		Feature Test Part3 (Dump file for Marcus use).ipynb
Feature Test Part3 (Plants Merged Training)-final test-Copy1.ipynb		Feature Test Part3 (Plants Merged Training)-final test-Copy1.ipynb
Feature Test Part3 (Plants Merged Training)-final test.ipynb		Feature Test Part3 (Plants Merged Training)-final test.ipynb
Feature Test Part3 (Plants Merged Training)-multiclass.ipynb		Feature Test Part3 (Plants Merged Training)-multiclass.ipynb
Feature Test Part3 (Plants Merged Training)-xgb-Copy1.ipynb		Feature Test Part3 (Plants Merged Training)-xgb-Copy1.ipynb
Feature Test Part3 (Plants Merged Training).ipynb		Feature Test Part3 (Plants Merged Training).ipynb
Feature Test Part3 (Training with sparse&dense text).ipynb		Feature Test Part3 (Training with sparse&dense text).ipynb
Feature test.ipynb		Feature test.ipynb
Final feat gen script.ipynb		Final feat gen script.ipynb
Get Image NIMA Scores.ipynb		Get Image NIMA Scores.ipynb
GridSearcher.py		GridSearcher.py
Hash Char WB Features.ipynb		Hash Char WB Features.ipynb
KNN Dist + Indices + Features Generator.ipynb		KNN Dist + Indices + Features Generator.ipynb
KNN Dist + Indices Generator- (sparse ann).ipynb		KNN Dist + Indices Generator- (sparse ann).ipynb
LDA on description.ipynb		LDA on description.ipynb
LDA+NMF Feature Generator.ipynb		LDA+NMF Feature Generator.ipynb
Leak.ipynb		Leak.ipynb
Merge Final Features for RNN,Ridge,MLP,LR.ipynb		Merge Final Features for RNN,Ridge,MLP,LR.ipynb
Model Stacking-519.ipynb		Model Stacking-519.ipynb
Model Stacking-719.ipynb		Model Stacking-719.ipynb
Model Stacking-Small.ipynb		Model Stacking-Small.ipynb
Model Stacking.ipynb		Model Stacking.ipynb
NMF on description.ipynb		NMF on description.ipynb
OOF Prediction Analysis.ipynb		OOF Prediction Analysis.ipynb
Periods experiment.ipynb		Periods experiment.ipynb
Prestage-LR oof training.ipynb		Prestage-LR oof training.ipynb
Prestage-Ridge oof training.ipynb		Prestage-Ridge oof training.ipynb
Price Feature Generation.ipynb		Price Feature Generation.ipynb
README.md		README.md
RNN Baseline + Pretrained WordVec.ipynb		RNN Baseline + Pretrained WordVec.ipynb
RNN Self-Trained WordVec + Image + Merge Features (with Fast Loading)-Copy1.ipynb		RNN Self-Trained WordVec + Image + Merge Features (with Fast Loading)-Copy1.ipynb
RNN Self-Trained WordVec + Image + Merge Features (with Fast Loading).ipynb		RNN Self-Trained WordVec + Image + Merge Features (with Fast Loading).ipynb
RNN Self-Trained WordVec with raw Image (with Fast Loading and adv features).ipynb		RNN Self-Trained WordVec with raw Image (with Fast Loading and adv features).ipynb
RNN Self-Trained WordVec with raw Image (with Fast Loading).ipynb		RNN Self-Trained WordVec with raw Image (with Fast Loading).ipynb
RNN Self-Trained WordVec with raw Image.ipynb		RNN Self-Trained WordVec with raw Image.ipynb
RNN Self-Trained WordVec.ipynb		RNN Self-Trained WordVec.ipynb
RNN Training.ipynb		RNN Training.ipynb
Simple Feature Generation.ipynb		Simple Feature Generation.ipynb
Stacker Blender.ipynb		Stacker Blender.ipynb
TF IDF Features.ipynb		TF IDF Features.ipynb
Text Features (Counter Vectorizer (char level based)).ipynb		Text Features (Counter Vectorizer (char level based)).ipynb
Text Features (TF-IDF).ipynb		Text Features (TF-IDF).ipynb
Text Features Training (CHAR WB).ipynb		Text Features Training (CHAR WB).ipynb
Text Features Training.ipynb		Text Features Training.ipynb
Text Fusion Features.ipynb		Text Fusion Features.ipynb
Truncated SVD on other NN's prediction.ipynb		Truncated SVD on other NN's prediction.ipynb
Truncated TF-IDF Generation.ipynb		Truncated TF-IDF Generation.ipynb
WordVec Training.py		WordVec Training.py
all features with feature selection training.ipynb		all features with feature selection training.ipynb
baseline script.ipynb		baseline script.ipynb
counter vec char_wb 24 finetune.ipynb		counter vec char_wb 24 finetune.ipynb
hash vec char_wb23_finetune.ipynb		hash vec char_wb23_finetune.ipynb
image meta analysis.ipynb		image meta analysis.ipynb
item seq no + img top 1 explore.ipynb		item seq no + img top 1 explore.ipynb
script.ipynb		script.ipynb
testing.ipynb		testing.ipynb
tfidf finetune.ipynb		tfidf finetune.ipynb
tfidf-finetune-gbdt.ipynb		tfidf-finetune-gbdt.ipynb

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