1.Considering that ImageNet consists of many fine-grained object categories and that some images contain multiple object categories, this is an incredible feat, nearly on par with human performance. While at first glance the model may appear incredibly complex, upon closer inspection, the overall structure of the model can be broken down into a few basic sections: the stem, the inception modules, the auxiliary classifiers, and finally the output classifier.

2. GoogLetNet is Inception-V1. Its TensorFlow implementation is at https://gist.github.com/joelouismarino/a2ede9ab3928f999575423b9887abd14

   Its related blog is at http://joelouismarino.github.io/blog_posts/blog_googlenet_keras.html

   Inception-V3 is at https://github.com/tensorflow/models/tree/master/inception  

3. Take advantage of Keras to recall GoogLeNet