roman-4erkasov Goto Github PK

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My name is Roman, I'm a Data Scientist and ML Engineer with Python/C/C++ backend.

🔭 I'm currently working with Graph Neural Networks based on Economical Graphs. I both like developong models as a Data Scientist and implement them into Production as an ML Engineer.

🌱 I'm currently learning the following courses:

• C++ Developer course with excellets projects, for example "Mython interpreter": https://practicum.yandex.ru/cpp/
• Computer Vision for Middle Data Scientists: https://deepschool.ru/

Fields of interests: AI in Biology, Algotrading, Network Science, GNN, NLP, CV, MLOps, C++, HPC, Distributed Systems

📫 How to reach me: LinkedIn

I grouped my projects by topics to make your search more convenient🤗

• C/C++ Projects
• Network Science / GNN
• Python Projects
• Algorithmic Projects
• ML/DS Projects
• NLP Projects
• CV Projects
• HPC Projetcs

• Languages: Python, C/C++, SQL, Bash, Java (a long time ago), SAS (a long time ago)
• Have an experience in Labeling Crowdsourcing: Toloka/TolokaKit, LabelStudio, Phone Questionaires
• DS/DL Modeling: NLP, CV, GNN, Transformers, OCR, Time Series Analysis, Ranking, Metric Learning, Meta Learning
• DS/ML Tooling: PyTorch, DGL, PyG, Hugging Face, PyTorch Lightning, XGBoost/LightGBM/CatBoost, Scikit-Learn, SciPy, Pandas, Pybind11, ClearML, Catalyst, DVC, ONNX/TRT/OpenVino/TorchScript/TorchTrace, TorchServe
• XOps: Unix/Linux/AIX, Bash, AWK, Jenkins, Git, Airflow, Docker, Docker Compose, Ansible, DVC,
• HPC/Big Data: OMP, MPI, Hadoop, PySpark, Hive, Slurm, HDFS
• Distributed Learning: PyTorch Distributed, Gloo, NCCL, Khorovod, TGL, BNS-GCN
• Python: PyTest, FastAPI, Dependency Injector, PyDantic, Flask, KFService, sqlalchemy, BeautifullSoup, lxml, Ansible, Hydra/OmegaConf/PyYaml
• C/C++: OMP, Protobuf, Boost, POCO, GTest/GMock
• My Fave IDE: Vim and NeoVim ❤️

• Data Science Specialisation from Big Data Academy MADE
• Specialisation "Machine Learning and Data Analysis"
• Natural Language Processing
• Intoductin to Big Data
• Algorithmic Toolbox
• Intoduction to Deep Learning
• Machine Learning with Big Data
• Big Data Integration and Processing
• Big Data Modeling and Management Systems