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data-driven-decisions

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SOMOSPIE (Soil Moisture Spatial Inference Engine) consists of a Jupyter Notebook and a suite of machine learning methods to process inputs of available coarse-grained soil moisture data at its native spatial resolution. Features include the selection of a geographic region of interest, prediction of missing values across the entire region of int…

  • Updated May 1, 2025
  • Jupyter Notebook

End-to-end portfolio construction systems exemplify modern quantitative investing where machine learning and optimization are tightly coupled to drive better portfolio outcomes. This repository contains a Jupyter notebook that illustrates a mean-variance end-to-end system and compares it to bechmark models.

  • Updated Jun 4, 2025
  • Jupyter Notebook

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