The problem Statements
Given a set of labeled images of cats and dogs, a machine learning model is to be learnt and later it is to be used to classify a set of new images as cats or dogs.
The accuracy on the test dataset is not going to be good in general for the above-mentioned reason. In order to obtain good accuracy on the test dataset using deep learning, we need to train the models with a large number of input images (e.g., with all the training images from the kaggle dataset).
A few sample labeled images from the training dataset are shown below.
Steps of this program:
i. Get the data into python. ii. Prepare the data for the algorithm. iii.Define the Model. iv. Train the model and get the results.
https://www.kaggle.com/c/dogs-vs-cats/data