AIM :

Classification of images using Convolutional Neural Network.

Introduction

It is very easy to recognise the image for a human one, but for a computer it is very difficult to do that. Convolutions Neural Network allows us to analyse the image content. CNN can be implimented using the sklearn library, CNN model take images as input to model and after the classfication we get the result in predicted classes.

Keywords

Keywords : Machine Learning, CNN, Image Processing, Matplotlib.

Tools

PreRequirements :

	 LIBRARIES 	: Sklearn, Keras, matplotlib.
	 IDE 		: spyder

Classfy the images and store them into respective folders, built the model using keras

procedure to run

Procedure to Exicute the Program:

1). Exctraction :
	Dataset is Downloaded form Kaggle
2). Preporcessing
	Images are proprocessed and no need to resize and if needed we can resize them using numpy.
3). Model Training
	Run the model.fit statement
4). prediction
	To predict the images content run the model.predict command with argument as a numpy matrix

Evaluation Plan

As this is a Classification Problem we can calculate the accuracy of model from sklearn.metrics using accuacy Score.