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2nd place solution for the MeLi Challenge 2019
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README.md

mercadolibre

2nd place solution for the MeLi Challenge 2019

This solution uses three models SGD (scikit-learn), multinomialNB (scikit-learn) and GRU (Keras) trained on both char level and word level, and in two different (but quite similar) datasets.

Instructions to generate submission

Required packages and softwares:

Python3 with the libraries Numpy, Pandas, Scikit-Learn, MatplotLib, Keras, NLTK. (No other library was used. No pre-trained model was used.)

Follow the steps:

  1. Unpack train, test and sample submission in the root folder with the respective names: train.csv, test.csv, sample_submission.csv

  2. Run all notebooks in MeLi_BaseGen/

  3. Run all notebooks in MeLi_scripts2/

  4. Run all notebooks in MeLi_scripts3/

  5. Run the notebook MeLi_Ensembles/MeLi_Ensemble_06.ipynb

  6. Run the notebook MeLi_Ensembles/MeLi_Ensemble_11.ipynb

  7. Run the notebook MeLi_Ensembles/MeLi_FinalEnsemble.ipynb

The final submission will be in the root folder with the name 'submission_MegaEnsemble02.csv' :)

PS: Some of these notebooks might require more than 64 GB of memory to run. Each notebook takes about 1 to 2 hours to run copletely in a 4 cores computer.

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