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  • University of Southern California
  • Los Angeles, CA

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rsyamil/README.md

Hello, I'm Syamil 👋

  • My interdisciplinary expertise is at the intersection of machine learning, earth science and flow physics. I interface current ML/DL tools with domain-specific tools to solve complex problems in dynamical systems.
  • I aspire to make ML/DL more accessible and explainable to practitioners.

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  1. cnn-regression cnn-regression Public

    A simple guide to a vanilla CNN for regression, potentially useful for engineering applications.

    Jupyter Notebook 40 11

  2. timeseries-rnn timeseries-rnn Public

    Time-series forecasting with 1D Conv model, RNN (LSTM) model and Transformer model. Comparison of long-term and short-term forecasts using synthetic timeseries. Sequence-to-sequence formulation.

    Jupyter Notebook 23 7

  3. latent-space-data-assimilation-lsda latent-space-data-assimilation-lsda Public

    Ensemble-based history matching method with latent-space proxy model for nonlinear forward model and non-Gaussian models.

    Jupyter Notebook 12 5

  4. gans gans Public

    Keras implementation of dcgan, wgan and wgan-gp with digit-MNIST dataset for tutorials.

    Python

  5. dimensionality-reduction-classic dimensionality-reduction-classic Public

    Tutorials on classic dimensionality reduction techniques using tailored bases (SVD) and generic bases (Fourier and Wavelets).

    Jupyter Notebook 3 2

  6. cnn-classifier cnn-classifier Public

    A simple guide to a vanilla CNN for classification and transfer learning

    Jupyter Notebook 5 1