AlexNet and ImageNet Explained
Today’s deep learning revolution traces back to the 30th of September, 2012. On this day, a Convolutional Neural Network (CNN) called AlexNet won the ImageNet 2012 challenge. AlexNet didn’t just win; it dominated.

AlexNet was unlike the other competitors. This new model demonstrated unparalleled performance on the largest image dataset of the time, ImageNet. This event made AlexNet the first widely acknowledged, successful application of deep learning. It caught people’s attention with a 9.8 percentage point advantage over the nearest competitor.

Until this point, deep learning was a nice idea that most deemed as impractical. AlexNet showed that deep learning was more than a pipedream, and the authors showed the world how to make it practical. Yet, the surge of deep learning that followed was not fueled solely by AlexNet. Indeed, without the huge ImageNet dataset, there would have been no AlexNet.

The future of AI was to be built on the foundations set by the ImageNet challenge and the novel solutions that enabled the synergy between ImageNet and AlexNet.

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00:00 Intro
01:06 Birth of Deep Learning
02:52 ImageNet
07:56 Lack of Readiness for Big Datasets
09:57 ImageNet Challenge (ILSVRC)
11:47 AlexNet
19:30 PYTORCH IMPLEMENTATION
19:55 Data Preprocessing
27:06 Class Prediction with AlexNet
31:50 Goldfish Results
34:27 Closing Notes