vladmaneata

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Vladislav Maneata vladmaneata

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MSc Applied Mathematics | AI/ML enthusiast Neural Networks • Reinforcement Learning • Cryptographic AI Python • TensorFlow • NumPy

Moldova

vladmaneata/README.md

Hi, I'm Vladislav 👋

MSc Applied Mathematics | AI/ML enthusiast based in Moldova 🇲🇩

About me

🎓 Master's in Applied Mathematics, background in Mathematics & Informatics
🤖 Interested in Neural Networks, Reinforcement Learning, and Cryptographic AI
📊 Building toward Data Science and ML engineering
🐍 Working mostly in Python — TensorFlow, NumPy, scikit-learn

Projects

🌸 Iris Data Analysis — EDA and classification with Decision Tree
🛒 Superstore Sales Analysis — retail EDA with pandas and matplotlib
🗄️ Superstore Sales SQL — retail analysis with SQLite
📊 Superstore Sales Dashboard — interactive Streamlit dashboard
🏠 California House Price Prediction — linear regression model

Tech Stack

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ML_Portfolio ML_Portfolio Public

Machine learning projects and experiments — classification, regression, and data analysis

Python
iris-data-analisis iris-data-analisis Public

End-to-end EDA and classification on the Iris dataset — visualization, Decision Tree model, and feature importance analysis

Jupyter Notebook
Superstore-sales-analysis Superstore-sales-analysis Public

Exploratory data analysis of retail sales data — trends by category, time, region, and product, with key business insights

Jupyter Notebook
superstore-sales-sql superstore-sales-sql Public

Retail sales analysis using SQL (SQLite) in Python — category performance, regional insights, and seasonal trends

Jupyter Notebook
Superstore-sales-dashboard Superstore-sales-dashboard Public

Interactive sales dashboard built with Streamlit — filters by region and category, KPI metrics, and dynamic visualizations

Python
California-house-price-prediction California-house-price-prediction Public

Linear regression model to predict California house prices — correlation analysis, model evaluation, and feature interpretation