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Machine learning and statistical algorithms implemented in pure NumPy and well-known libraries such as Sklearn, Pytorch, and Statsmodels.

Linear Regression

  1. Implementation from scratch.

Graph Neural Networks

  1. Implementation from scratch of Relational Graph Convolutional (R-GCN) layer.
  2. Implementation with NumPy and DGL of the Graph Attention (GAT) layer.

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Jupyter notebooks for testing ML models

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