Accuracy of Deep Learning Models Over the Years

Over the years, there were many achievements in deep learning, many of which were directly related to the ImageNet Large Scale Visual Recognition Challenge (ILSVRC, or ImageNet challenge for short). We talked about some of those milestones in deep learning in the past and how their unique innovations have helped shape the deep learning landscape today.

Today let us look at how the accuracy of these significant models has increased over the years.

Deep Learning Models Over the Years

When reporting the accuracy of classification models two accuracy measures are typically used: Top-1 Accuracy, and Top-5 Accuracy.

• Top-1 Accuracy - Where the highest probability/confidence prediction from the model matches the expected class
• Top-5 Accuracy - Where the expected class is within the top 5 predictions of the model

Pre-orders are Now Open for Deep Learning on Windows

Pre-orders for my new book, Deep Learning on Windows, are Now Open at Amazon.com!

Deep Learning on Windows is my latest book, and it is the longest and the most comprehensive book I have written to date. The book is meant for both beginners and intermediates to deep learning. It covers topics from setting up your tools on Windows and getting started, to complex but fun topics in deep learning and computer vision.

The Cover of 'Deep Learning on Windows'

The Windows OS accounts for over 70% of the desktop PC usage. Windows provides many conveniences, with a wide variety of available productivity tools, causing it to gather a large userbase. This means that there is a large percentage of you - AI enthusiasts and developers - out there that primarily work on the Windows OS, and would prefer to develop deep learning models on Windows itself.