Workshop for Cat/Dog Classification using CNN

Notebook

Import all needed packages and declare constants

Create dataframe with the files.

Check the details of the data.

Check the categories of the classification.

Display the image.

Add Convolution details to the model with other hidden layers

Add callbacks for early stopping and learning rate optimization

Create train and test data

Check the validation data

Create dataframe of images with twists and turn for train data.

Create dataframe of images with twists and turn for validation data.

Display all the twists and turned images

Train the model using fit command

Save the weights

Display the accuracy graph

Create dataframe of images with twists and turn for test data.

Prepare the data to display the name in the visualisation

Print the result with prediction and image

Save the prediction result in csv