I joined Kaggle in October 2021. Since then, I wrote many notebooks in R and Python and began to play on some competitions.
One of my favorites is the Greg Kaggle Metabook. Using Meta Kaggle and some scraping, I wrote a notebook that summarize some selected notebooks and my most upvote works. This notebook is scheduled to run one a week.
Another notebook that I like is Brazil Climate Change - Part III - Stations EDA. This kernel began with an isolated notebook that collect and processed data from INMET (National Institute of Meteorology - Instituto Nacional de Meteorologia) repository. In this first step, data is stored as a Kaggle dataset. I used some data visualization tools in Brazil Climate Change - Part III - Stations EDA to get a better picture of data quality and then fill the missing values using IterativeImputer from scikit-learn.
You can see all of them at my profile. You can also reach me on LinkedIn or direct by e-mail.