erlemar / cpython Goto Github PK

I have a personal website now! You can find it here

And I have an Obsidian project with my ML-related notes.

I'm an economist by education and usually try to understand why things happen.

For a long time, I was fascinated by foreign languages and studied them: English (my native is Russian), German, Japanese, and Spanish.

Currently, I'm Data Scientist and an active Kaggler.

Also, I have a portfolio listing some of my projects, which include Kaggle kernels, pet-projects, and other things.

• Paper Review: Winning Amazon KDD Cup24
• Paper Review: Wolf: Captioning Everything with a World Summarization Framework
• Paper Review: Diffusion Feedback Helps CLIP See Better
• Paper Review: Masked Attention is All You Need for Graphs
• Paper Review: RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs

• [Перевод] Мой путь изучения иностранных языков: прошлое, настоящее и будущее
• Третья жизнь пет-проекта по распознаванию рукописных цифр
• Как мы не смогли создать медицинского чат-бота. История проекта, который так и не увидел свет
• Из экономистов в дата-сайнтисты или как стать лидером рейтинга Kaggle Notebooks
• Обзор на статью Visual Transformers — новый подход к тренировке моделей компьютерного зрения на основе visual tokens

2019:

• ML Training talks about gold winning solution in Kaggle Predicting Molecular Properties Competition
• An overview of 2019 year in Kaggle, Talk in Russian at ODS.AI event
• Data Halloween: predicting chaotic actions of clients. Talk in Russian at ODS.AI event
• Storytelling with data visualization: case of kaggle kernels. Talk in Russian at Data Fest 2019
• Interview with Kaggle Kernels Grandmaster #1: Artgor | Andrew Lukyanenko. Chai Time Data Science | player.fm link
• Kaggle: People, We’ve Gamified Progress

2020:

• Andrey Lukyanenko - Handwritten digit recognition w/ a twist & topic modelling over time
• Pair Programming: Deep Learning Model For Drug Classification With Andrey Lukyanenko
• DataFest 2020 talk: My Kaggle Story
• Overview of approaches to "Mechanisms of Action (MoA) Prediction" competition on Kaggle (3 weeks before the end of the competition)
• Metro Analysis and Visualization
• Writing reusable pipelines in Deep Learning | Mindhack! Summit
• December Lightning Talks. Training pipeline with Pytorch Lightning and Hydra

2021:

• Podcast talk about Kaggle, modern ML technologies, frameworks, hardware, and many other things
• Building your Data Science Career: how to become a data scientist