🧠 Neural Network Using Basic Python

A simple implementation of a Neural Network from scratch in pure Python — without using deep learning libraries.
This project is aimed at building intuition about how neural networks work under the hood, covering forward propagation, backpropagation, and training on toy datasets.

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🔹 Features

• Implemented using only Python + NumPy
• Supports:
  • Forward propagation
  • Backpropagation with gradient descent
  • Multiple hidden layers
• Simple training loop on sample data
• Clear, educational code with comments

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📊 Example Workflow

1. Initialize the network with chosen input, hidden, and output sizes.
2. Train the network using gradient descent.
3. Observe loss decreasing across epochs.

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For more detail understanding you may visit This Youtube Playlist