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iicght/README.md

Hi, I’m Ivan 👋

🎓 Economics student interested in data analytics, ML, finance, and automation. I like combining economics and programming to build useful analytical tools and find insights in data.

🛠 Tech Stack

Data & ML: Python · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn · Statistics

Including:

Regression · Classification · Clustering · Gradient Boosting · Feature Engineering

Finance & Economics: Financial Analysis · Credit Analysis · Investment Modeling · Taxation · Accounting Basics

Tools: SQL · MySQL · Jupyter Notebook · APIs · Telegram Bots

🚀 Interests

  • 📊 Data analysis and visualization
  • 🤖 Machine learning for business and finance
  • 💸 Investment and credit analysis
  • ⚙️ Automation, parsers, and trading-related tools
  • 🧾 Economics, taxation, and financial statements

🎯 Focus

Building practical projects that turn data into clear decisions.

📫 Contact:

Pinned Loading

  1. customer-segmentation-ml customer-segmentation-ml Public

    Automated customer segmentation and behavioral analysis using Unsupervised Machine Learning to optimize marketing strategies.

    Jupyter Notebook

  2. loan-default-prediction loan-default-prediction Public

    Machine learning models for credit scoring and bank loan default prediction using socio-demographic and financial data. Implemented detailed evaluation metrics logging to maximize bank profits.

    Jupyter Notebook

  3. PortfolioTheory PortfolioTheory Public

    Реализация модели оптимизации инвестиционного портфеля на основе теории Марковица.

    Python

  4. belarus-vodka-time-series belarus-vodka-time-series Public

    Quarterly Belarus vodka sales forecasting with Holt-Winters, ARIMA, SARIMAX and Prophet using pandas, statsmodels and scikit-learn.

    Jupyter Notebook

  5. salary-regression-rlms salary-regression-rlms Public

    RLMS salary analysis: EDA, preprocessing and comparison of OLS, Lasso, Ridge, SGD and ElasticNet with pandas, scikit-learn and statsmodels.

    Jupyter Notebook