Sample codes and dashboards for 4th place solution for Kaggle's Home Credit Default Risk competition. These are some dashboardas and codes we used through this competition, our approach has been mainly based on the following approach:
As most of ML enthusiasts know feature engineering is the most important part of every ML competition and most informal one, everyone does it his/her way so instead of talking about feature engineering, here we present some feature engineering dashboards based on many good public kernels and our own ideas that are used to create diverse models.
We created a lot of oofs (150+) by changing parameters and features used in different models and dashboards. some of those models are presented here as examples...
Easy-to-use cryptocurrency trading strategy simulator and backtester
A Smart, Automatic, Fast and Lightweight Web Scraper for Python
A toolkit full of handy functions including most used models and utilities for deep-learning practitioners!
In this repository, I include all my notes and whatever I learn, so that everyone can benefit from them
A collection of ML related stuff including notebooks, codes and a curated list of various useful resources such as books and softwares. Almost everything mentioned here is free (as speech not free food) or open-source.
Multi-class confusion matrix library in Python
In this repository, I have written about my experiences in studying Machine learning. Also, I have included the solutions of some Machine learning exercises and my educational projects.
Image Processing Practics