Utility scripts

This repository contains various useful scripts for data science projects.

jupyter_init.ipynb

• A jupyter boilerplate for data science projects.
• Functionalities:
  • Collapsible sections
  • Auto reload of imported file if it is modified
  • Ignore warnings
  • Select max rows and columns to print when printing complete dataframe
  • Change cells width
  • Install jupyter dark theme
  • Save/load pickle files

send_email.py

• Send email in python with attachment
• Allows mulitple receivers
• Allows multiple attachments

randomforest_optimal.ipynb

• Random forest code with randomsearch and gridsearch for finding optimal parameters.

fasttext_optimal_classify.ipynb

• Fasttext code with with autotune for finding optimal parameters.

fasttext_classify_bagging.ipynb

• Bagging for NLP data with fasttext, also used for EDA to check on which categories we are performing good.

rf_modeling.ipynb

• RF classification complete notebook (source: fastai ml1).

rf_interpretation.ipynb

• Data Interpretation using RF complete notebook (source: fastai ml1).

fastai_utils.py

• FastAi required functions to run notebooks without fastai installation.

find_validation_set.ipynb

• Notebook for finding optimal validation set. This technique is very useful for kaggle competitions where test scores are kaggle scores after submission. This will help us in finding a good validation set according to the kaggle's hidden test set.

rf_extrapolation.ipynb

• RF expolation issue demo notebook.