Description

  • Focused on achieving high precision in handwritten digit classification by implementing and optimizing multiple machine learning algorithms.
  • Addressed overfitting challenges with extensive data preprocessing and feature extraction.

Tech Stack

  • Python.

Contributions

  • Implemented and optimized machine learning algorithms for handwritten digit recognition.
    • Algorithms implemented: Linear regression, Logistic regression, SVM, KNN, RBF-Network, Neural network.
  • Enhanced model performance through data preprocessing and feature extraction and handled data overfitting.
  • Improved feature representation and prediction reliability, achieving high classification accuracy.