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Mastering the XOR Problem: A Deep Dive into Neural Network Mechanics 🧠💡
"𝒊𝒇 𝒚𝒐𝒖'𝒅 𝒍𝒊𝒌𝒆 𝒕𝒐 𝒈𝒆𝒕 𝒕𝒉𝒆 𝒘𝒐𝒓𝒌𝒊𝒏𝒈 𝑬𝒙𝒄𝒆𝒍 𝒂𝒏𝒅 𝒔𝒆𝒆 𝒕𝒉𝒆 𝒘𝒐𝒓𝒌𝒊𝒏𝒈 𝒐𝒇 𝑨𝒓𝒕𝒊𝒇𝒊𝒄𝒊𝒂𝒍 𝑵𝒆𝒖𝒓𝒂𝒍 𝑵𝒆𝒕𝒘𝒐𝒓𝒌! :- You can access the repository using the following link:
GitHub Repository Link :
https://lnkd.in/enSiHXBe

It’s often the first challenge in neural network fundamentals, and I’m excited to share my end-to-end solution for the classic XOR problem!
I've moved beyond just the theory and built a fully functional model from scratch, using Excel and Python to illustrate every step:
📉 The Core Mechanism:
Forward & Backward Feed: An Excel sheet meticulously details the calculations for both forward propagation (predictions) and backward propagation (error correction) using the backpropagation algorithm.
Epoch Analysis: The Excel demonstrates precisely how the total error systematically reduces with each training epoch. It’s fascinating to watch the network learn in real-time!
Visualization: A Python script was used to visualize the learning curve, clearly showing the error convergence.

This project was a great exercise in solidifying the foundational math and logic behind how neural networks actually learn.
Watch the video to see the process in action. I'm happy to share the files with anyone interested in digging into the mechanics!

For Complete YouTube video (Like and Subscribe) : https://lnkd.in/ejM5qdnT

#AI #MachineLearning #DataScience #NeuralNetworks #Backpropagation #XOR #Excel #Python #Tech #Learning #DeepLearning #DataAnalytics