/timofeiryko

About

My name is Timofei Ryko and here you can find a list of my coding and data science skills and my portfolio. Complete information about my work experience, achievements, etc can be found in my Master CV.

📫 How to reach me?

My nickname is timofeiryko on every platform except instagram (in inst it is rykotimofei, but it will be fixed soon) and I am just Timofei Ryko everywhere.

What do I know and can do?

Programming languages

  • Python — advanced level
  • R — medium level
  • MATLAB — medium level
  • Rust — basic knowledge
  • Java — basic knowledge

Markup and frontend

  • HTML — medium level
  • Bootstrap — medium level
  • CSS — basic knowledge
  • JavaScript — basic knowledge
  • Markdown
  • LaTex

Skills

👨‍💻 Coding

  • Python Asyncio — basic knowledge
  • Web development
    • Django — medium
    • FastAPI — basic
    • SQLAclhemy — medium
    • AIOGram — advanced (telegram bots)
  • Web scraping and API
    • Working with RESP API, JSON /LXML
    • Beautiful Soup
    • Selenium — medium
  • Bash and Unix
  • Git and GitHub

📈 Data Science

  • Explorational Data Analysis (EDA) and statistics
    • Pandas — advanced
    • Seaborn and matplotlib — advanced
    • Statsmodels, SciPy
    • SQL — medium level
  • Machine learning
    • Scikit-learn — advanced (custom transformers, encoders, etc)
    • Boosting algorithms (XGBoost, CatBoost, LightGBM)
    • TensorFlow and Keras — basic
    • Automation with featuretools and auto-sklearn
    • Bayesian hyperparameter tuning with Optuna
    • Simple NLP with SpaCy, tokens clusterization techniques
    • Computer Vision (application to histopathology)

🧬 Bioinformatics and computational biology

  • Single-cell analysis with Scanpy
  • Working with Entrez APIs using biopython utilities
  • ODE modeling with MATLAB
  • Ensembl Variant Effect Predictor with plugins configuration
  • Genes annotation with biomart, Ensembl REST API and other tools
  • Analyzing sequence association data

✅ Portfolio

  • BioQuest  —  website on Django
    • Django 4
    • Bootstrap 5
    • OOP principles
  • EDAwesome  —  my Python library for quick and nice explorational data analysis
    • EDA: pandas, seaborn, matplotlib
    • Packaging with poetry
  • Home credit dataset analysis and loan repayment prediction  —  capstone project from the Turing College
    • EDA: pandas, seaborn, matplotlib
    • Scikit-learn  —  advanced (custom transformers, encoders, etc)
    • Automation with featuretools and auto-sklearn
    • Bayesian hyperparameter tuning with Optuna
    • Simple NLP with SpaCy, tokens clusterization techniques
    • I got 93/100 on code review at Turing College
  • Podcast analysis  —  data analysis project from the Turing College
    • SQL
    • EDA: pandas, seaborn, matplotlib
  • Science parser telegram bot
    • SQLAclhemy
    • AIOGram
    • Python Asyncio
    • Working with RESP API, JSON /LXML
    • Beautiful Soup
    • Selenium
    • Working with Entrez APIs using biopython utilities
  • Tgscraper  —  Python package for telegram scraping
  • Modeling for the iGEM competition
    • ODE modeling with MATLAB
  • SMTB bioinformatics project
    • Analyzing sequence association data
    • EDA: pandas, seaborn, matplotlib
    • Beautiful Soup
    • Ensembl Variant Effect Predictor with plugins configuration
  • Computer vision for histopathology
    • EDA: pandas, seaborn, matplotlib
    • TensorFlow and Keras
    • It was the final project for the course «Machine Learning in Synthetic Biology» at the University and I got an A for it
  • Application of SpaCy to kaggle-nbme competition
  • CITEseq data analysis
    • Single-cell analysis with Scanpy
    • Genes annotation with biomart, Ensembl REST API and other tools
  • Outlook emails parser (the source code is unavailable for legal reasons)
  • Machine learning system for determining SpO2 by video (the source code is unavailable for legal reasons)