Performing Image Classification for 10 Different Monkey Species using CNN

the main aim of this project is to achieve finegrain image classification by applying a suitable machinelearning architecture to the set of images present in thedataset. The chosen dataset is taken as a part of the Kagglecompetition and is selected from Wikipedia's monkeycladogram and this dataset contains 10 different species ofmonkeys which are to be classified with the help of amachine learning architecture augmented by Imageprocessing. After having brief exposure and using severalarchitectures to classify this dataset, the ConvolutionalNeural network was found to be the best fit.