Dataset Details:
you can download dataset from google apis.

Dataset Description:
Dataset contain 3000 images of Cats and Dogs, we will train our model on 1700 images,710 images for validation and 604 images for testing.

Training Images of cats = 850
Training Images of dogs = 850

Validation Images of Cats = 352
Validation Images of Dogs = 358

Testing Images of Cats = 304
Testing Images of Dogs = 300

Overfiting and Underfitting aviodence Techniques Used:
1-Data Augmentation (zoom,horizontal_flip,rotation)
2-Dropout

Model Summary:
I used convolutional neural networks with 32, 64 and 128 layers.


Training and Validation Graph:

Results:
Achieved 84% Accuracy on Training data with epochs = 100
81% accuracy on validation data
80% accuracy on testing data