Developed methods in R to predict images of CIFAR data consisting of 10 image classes
Implemented machine learning algorithms - random forest, support vector machines, logistic regression in R; compared their performance and analysed the best fit model using dimensionality reduction (PCA) and cross-validation error
Developed a convolution neural network using Keras in R for image classification task and achieved an accuracy of 85%