Analysis
This article celebrates a successful implementation of a multi-layer neural network using Numpy to solve the XOR problem. The author's journey highlights the challenges and triumphs of tackling this fundamental AI task, emphasizing the importance of understanding matrix dimensions and gradient calculations. The detailed explanation and code examples provide a valuable learning resource.
Key Takeaways
- •The article documents the author's journey from single-layer perceptrons to tackling the XOR problem with multi-layer neural networks.
- •Challenges included understanding matrix dimensions and gradient calculations, key aspects of deep learning.
- •The successful implementation provides valuable insights and code examples for others learning AI.
Reference / Citation
View Original"Ultimately, when the scratch implementation of XOR was completed, I was filled with a sense of accomplishment, like defeating the origin of the AI winter that had lasted for a long time, and a sense of accomplishment that I had implemented in code in 2026 the thoughts that Rosenblatt had tried to achieve in the 1960s but could not realize, and the background that I had once been frustrated by XOR also overlapped, and I felt very deeply moved."