Practical Guide to Transfer Learning in TensorFlow for Multiclass Image Classification

Oftentimes we do not have access to a wealth of labeled data or computing power to build image classification deep learning models from scratch.
Fortunately, transfer learning empowers us to develop robust image classifiers for our specific classification tasks, even if we have limited resources.
In this easy-to-follow step-by-step guide, we will learn how to utilize pre-trained models as part of transfer learning in TensorFlow to classify images effectively and efficiently.

Tutorials in the form of Jupyter notebooks are found in the notebooks folder
- Oxford-IIIT pets dataset
- Stanford cars dataset

Any question or suggestions to improve the explanations? I look forward to hearing from you!

Name		Name	Last commit message	Last commit date
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images		images
notebooks		notebooks
.gitignore		.gitignore
README.md		README.md

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