banknotes-classification

Data analysis and classification of counterfeit and genuine banknotes

CSE 575 Statistical Machine Learning

CLASSIFICATION USING K-NEAREST NEIGHBORS (KNN) ALGORITHM. This project is for classifying banknotes using the KNN algorithm.

Deployment of ML Model using Fast API. To run the API use `uvicorn app:app --reload`

Comparison of numerous supervised machine learning classifier models (Logistic Regression, K-Nearest Neighbors, Support Vector Machines and Decision Trees) predicting if a banknote is genuine or not based on the dataset from OpenML containing wavelet analysis results for genuine and forged banknotes. (Python 3)

TRY vs. USD Banknote Classification: A banknote classification application using CNN and VGG16 architectures. Model development process incorporating data augmentation, dropout, and learning rate optimization.