Keras-CNN-cats-vs-dogs-image-classification

This project is an image classification project using a deep-learning based on Convolutional Neural Networks (CNNs) with Keras.
The Dogs vs. Cats is a classic problem for anyone who wants to dive deeper into deep-learning.
The classifier is based on a rather simple CNN architecture and achieved a test accuracy of 94.84 %.

• You can find a link provided by microsoft to the dataset used in ths project here .
• You can find a link to the code output, including history logs and model weights here .

Model performance:

Validation accuracy and loss

Confusion matrix

Model predictions visualized :

Predicting dog images

Predicting Dog images

Predicting cat images

Predicting Cat images