My talks






My interviews
ML competitions
Kaggle ranks

Oct 10, 2019 - Discussion Grandmaster

Aug 29, 2019 - Competition Master

May 08, 2019 - 1st place in Notebook ranking

Feb 21, 2019 - Notebook Grandmaster

Notable competitions

Aug 29, 2019 - 8/2737. Gold medal in Predicting Molecular Properties

Aug 30, 2018 - 64/7176. Silver medal in Home Credit Default Risk

Aug 21, 2018 - 108/4464. Silver medal in Santander Value Prediction Challenge

Oct 20, 2018 - 100/3219. Silver medal in TGS Salt Identification Challenge

Mar 14, 2019 - 120/2410. Silver medal in Microsoft Malware Prediction

Aug 28, 2019 - 87/921. Bronze medal in Generative Dog Images

May 09, 2019 - 23/58 Anti-spoofing challenge

Mar 30, 2018 - 25/92 Geohack competition

Apr 24, 2018 - 3/67 Shop check categorization

Notable kaggle notebooks

EDA and models

1000+ upvotes, 100k+ views. A notebook for IEEE-CIS Fraud Detection competition. EDA, feature engineering, plots with altair, modelling with LGBM.

EDA, feature engineering and everything

900+ upvotes, 110k+ views. A notebook for Two Sigma: Using News to Predict Stock Movements competition. Text and tabular data EDA, analysis of stock market, plots with plotly, modelling with LGBM.

Segmentation in PyTorch using convenient tools

600+ upvotes, 60k+ views. A notebook for Understanding Clouds from Satellite Images competition. EDA, augmentations with albumentations, image segmentation using Catalyst.

Exploration of data step by step

600+ upvotes, 30k+ views. A notebook for PetFinder.my Adoption Prediction competition. A very detailed EDA of tabular and text data, complex plots with matplotlib and seaborn, modelling with LGBM.

How to not overfit?

500+ upvotes, 30k+ views. A notebook for Don't Overfit! II competition. Model interpretation, comparison of many models, comparison of feature selection methods, approaches to feature engineering on anonymized data.

EDA, Feature Engineering and model interpretation

400+ upvotes, 40k+ views. A notebook for TMDB Box Office Prediction playground competition. A very detailes EDA for various types of data, advanced approaches to feature engineering, model interpretation.

EDA, feature engineering and xgb + lgb

100+ upvotes, 8k+ views. A notebook for DonorsChoose.org Application Screening competition. This notebook won a second place in popularity ranking and got me a prize - Pixelbook.

Notable courses completed


Finished at 5th place. This was a useful course with useful theoretical materials and practical exercises.

Deep Learning Nanodegree with Pytorch on Udacity.


You can read about my experience of going through this course here.

Other activities and achievements

Moscow DataFest 6 (2019) - organized "EDA & Visualization" track.

Open Data Science Awards 2019 Got awards for one on best talks in ML Trainings and for progress in competitions.

Moscow DataFest 2020 - one of organizers of "ML trainings" track.

Open Data Science Awards 2020 Gor awards for one of best talks in Business section and for mentoring.

Completed Hacktoberfest in 2018 and 2020.

Wrote for a week in dsunderhood

I'm one of the main contributors of an open-source project for a topic modelling on news articles