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numpy-library

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This repository contains a Python implementation of Principal Component Analysis (PCA) for dimensionality reduction and variance analysis. PCA is a powerful statistical technique used to identify patterns in data by transforming it into a set of orthogonal (uncorrelated) components, ranked by the amount of variance they explain.

  • Updated Jun 6, 2024
  • Python

The dashboard delivers valuable insights into inventory levels, supplier performance, production schedules, and distribution logistics, enabling automotive companies to optimize their supply chain operations, reduce costs, and enhance overall efficiency.

  • Updated May 28, 2024

"This repository contains implementations of Boosting method, popular techniques in Model Ensembles, aimed at improving predictive performance by combining multiple models. by using titanic database."

  • Updated May 22, 2024
  • Jupyter Notebook

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