Artificial Neural Network from Scratch in Python for non linear data of XOR Gate

In this hands-on video, I demonstrate how to implement an artificial neural network (ANN) completely from scratch in Python—with no external libraries like NumPy, TensorFlow, or PyTorch.

We walk through each step:

Initializing weights and biases manually
Implementing the forward pass
Applying activation functions
Calculating error using mean squared error (MSE)
Manually computing gradients and updating weights (backpropagation)
This is an excellent learning experience for students and developers who want to understand how neural networks work under the hood without relying on black-box tools.

Whether you're new to AI or reviewing fundamentals, this video will strengthen your core understanding of how ANNs learn and process non-linear data.

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Видео Artificial Neural Network from Scratch in Python for non linear data of XOR Gate канала Physics Cardio