sidd312 / cifar-10-image-classification-project

Image classification machine learning class project

CIFAR-10-Image-Classification-Project

--> Applied different machine learning classification techniques like Ensemble, Support Vector Machine, Neural Networks, Multinomial Logistic Regression and Feature transformation techniques like Principal Component Analysis (PCA), Histogram of Oriented Gradients (HOG) and Scale Invariant Feature Transformation (SIFT) for the classification of 10 class image CIFAR-10 dataset.

--> Performed grid search to optimize the parameters for Support Vector Machine on HOG transformed data and obtained 59% test accuracy with our team standings as 33/123 total teams in the class.