Discover how a 1998 model still holds its ground in modern deep learning.
A Tale of LeNet-5: The Early Days of CNNs and a Journey Through Code
In 1998, the world was a very different place. The internet was just catching fire, flip phones were the latest craze, and artificial intelligence was more of a sci-fi buzzword than a household name. But in a small corner of the AI world, something revolutionary was brewing — a neural network called LeNet-5 was quietly changing the future of machine learning, one digit at a time.
Yann LeCun, the mastermind behind this breakthrough, didn’t have the massive GPU power we take for granted today. Yet, he crafted LeNet-5, a convolutional neural network (CNN) that could do what seemed like magic at the time: recognize handwritten digits with remarkable accuracy.
Fast forward to today, and LeNet-5 is still a cornerstone in the world of deep learning. Its architecture is often the go-to when learning about CNNs and image classification, and while models have become more complex, LeNet-5’s elegant simplicity continues to inspire.
Now, let’s not just talk about it — let’s dive into its architecture and implement it with…