The repository features a variety of analytics and machine learning projects showcasing end-to-end data science workflows.
📁 Data Filing - Efficient data organization and storage
🧹 Data Cleaning - Missing values, outliers, and inconsistency handling
🔄 Data Transformation - Feature engineering and preprocessing
👁️ Multiple Vision Comparison - Cross-platform analysis and validation
🗺️ Mapping - Geographic and relational data visualization
💡 Finding Insights - Statistical analysis and pattern recognition
⚡ Creating New Features - Advanced feature engineering techniques
| № | Title and link | About project | Key Results | Skills and Tools |
|---|---|---|---|---|
| 1 | Rating analysis | Assessing the correct display of ratings on the online platform Fandango. | 📊 Bias detection | Python Pandas Seaborn NumPy Matplotlib |
| 2 | Spotify streaming analysis | The music comparison between New York and Chicago. | 🎵 City preferences | Python Pandas Seaborn Matplotlib |
| 3 | Orders Data Analysis | Exploring and analyzing large datasets stored in Parquet format using Apache Spark and Pandas. | ⚡ Big Data processing | Python Spark Pandas Data Modeling |
| 4 | Ames housing price prediction | Machine Learning project predicting real estate prices in Ames, Iowa using comprehensive data analysis and ElasticNet regression. | 🎯 90.5% accuracy 💰 $17K MAE | machine-learning data-science python regression real-estate |
| 🏆 Projects | 📊 Datasets | 🎯 Best Accuracy | 🛠️ Technologies |
|---|---|---|---|
| 4+ | 10,000+ records | 90.5% | 8+ tools |
💼 Open for opportunities in Data Science, Machine Learning, and Analytics
📧 Contact: molochnyh2@gmail.com
💼 LinkedIn: Dmitrii Molochnykh
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