August 2018
Intermediate to advanced
438 pages
12h 3m
English
Content preview from Hands-On Transfer Learning with Python
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Formulating our real-world problem
As we mentioned earlier, we will be working on an image categorization problem with the constraint of having a small number of training samples per category. The dataset for our problem is available on Kaggle and is one of the most popular computer vision based datasets out there. The dataset we will be using comes from the Dogs vs. Cats challenge (https://www.kaggle.com/c/dogs-vs-cats/data), whereas our primary objective is to build a model that can successfully recognize and categorize images into either a cat or a dog. In terms of ML, this is a binary classification problem based on images.
To start, download the train.zip file from the dataset page and store it in your local system. Once downloaded, ...
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