I am a student, I am engaged in pet projects in a club at the university. I practice machine learning, algorithms, deep learning and many other things from data science.

In my free time, I can write my own programming language, make a project on arduino, or raise a telegram bot.

1. Drawing up an investor's risk profile for his transactions. Using the LightGBM algorithm on aggregated data in conjunction with the deep learning LSTM model, which predicted the investor's class by the sequence of his transactions. We used the PCA algorithm, feature engineering. It turned out to raise the F1 score from 0.4 to 0.65

2. In the framework of the project-generation of maps with the help of the VAE and the subsequent DCGAN.Creating images with a dimension of 64x64 pixels. the modified VAE made blurry pictures, so it was decided to use deep convolution GAN, which already created clear pictures. All architectures were written from scratch.

3. Sugestive servise is an algorithm that offers auto-completion based on the entered data. Using the trie and reversed trie algorithms.

4. Creating product embeddings. Detection of anomalies in transactions. ETL hackathon solution from Glow byte using pyspark and airflow.

Coding: Python (Pandas, Numpy, Matplotlib, Sklearn, catboost, xgboost, LightGBM, PyTorch, Seaborn, PySpark, transformers, Optuna, ML flow, FastApi, DVC), SQL, HTML/CSS, Git, Docker, Airflow,

Theory: Statistical, Data analysis, ML algorithms (Gradient boosting, Random forest, Regressions, Clustering, Anomaly Detection, etc.), Sequential Neural Networks, Convolution Neural Networks, NLP, GAN, Attention Mechanism, RecSys