Dog and Cat Image Classifier

Project Description:

A class project that used machine learning on MATLAB to teach a classifier that tells the difference between dogs and cats. Several types of ML were used like PCA, linear regression, and nearest neighbors. There was a training set consistent for all ML methods to ensure consistency in training. Likewise, there was a common testing set to check accuracy of each type, with accuracy ranging from 70-95%.

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Responsibilities:

• Experiment with different forms of machine learning like linear regression in MATLAB to build a dog and cat image classifier.