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randomdata

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This project implements a Temporal Convolutional Network (TCN) for time series forecasting. Using synthetic data (including trend, seasonality, and noise), the model’s ability to learn complex patterns and provide probabilistic forecasts is demonstrated with the Darts library.

  • Updated Aug 17, 2025
  • Jupyter Notebook

This project demonstrates the K-Means clustering algorithm using synthetically generated data. It explores the application of K-Means on random datasets with multiple centers, visualizing cluster results with scatter plots. The project emphasizes clustering performance evaluation through visual inspection and analysis of cluster separations.

  • Updated Aug 17, 2025
  • Jupyter Notebook

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