Coding Implementation of CNN [Keras Classification] Machine Learning by Debabrata Bhakat [EP 13/14]
Channel: Learn By Watch
Category: Education
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Description: Coding implementation of CNN In this we will be using the cifar10 dataset which is available from keras and can also be found here. In this problem we need to classify the images into 10 classes which is ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']. And we will be using CNN for that. ● First we split our dataset into train and test ● We take a look at some of the images in our dataset ● Next we build our model using keras methods ○ Initially there is a 3 layer convolution and max pool layer ○ At the end we have 2 dense layers and the last one has a ‘softmax’ activation function to classify into 10 classes. ● Compile our model using ‘adam’ as the optimizer ● We train our model and plot a graph of the loss of train and test dataset and see how our loss is continuously decreasing.
