What is this ?

This is my LGBM solution for Riiid kaggle competition. This model ensembled with a transformer allowed me to reach the 39th position out of 3395 (2% silver tier).

The files are:

• Main.ipynb: the main notebook in which I extract all of 70 + features of the model and train it. Running this notebook took me around three days in total, trained on the entire dataset
• Question correlation.ipynb: Visualizing the correlation between the 300 most common questions.
• Test inference: Notebook in which I tested the inference pipeline, and feature generation from dictionaries on the validation set.
• create-corr-df.py: Creating the correlation features data frame which will be joined with the main features data frame.
• gen-valid-split.py: Splitting the raw training data into validation folds.
• generate-corr.py: Generating questions' correlation data frame
• heat_pickle: pickle file containing the data frame of correlation data.

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Used hardware: Google cloud 256 GB ram, 16 vCPUs. The dataset is really big, and it needs so much memory and expensive hardware.

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Notes on the dataset:

• 100M rows
• 300k + Users
• 18k questions

For more information, please refer to the challenge page. My kaggle account: https://www.kaggle.com/abdessalemboukil