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Numerical methods & modelling

Academic experiments with neural networks and linear and polynomial relationships in data.

PythonNumPyscikit-learnMatplotlib
ResearchSELECT A STEP

The problem

Understanding model behaviour requires examining how assumptions and individual features affect predictions.

My contribution

  • Developed a neural-network experiment for dataset benchmarking.
  • Explored linear and polynomial relationships between housing-price features.
  • Used Python scientific libraries for modelling and visualization.

Evidence & scope

The work is listed in my professional profile as an academic modelling project. Its repository link is provided for further inspection.

What came out of it

Built modelling experiments with clear visualizations of relationships between input features and predictions.

Built practical familiarity with numerical methods, model experimentation, and clear visualization of data relationships.

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