Build a Neural Network From Scratch in Python | Machine Learning Tutorial
🧠 Build a Neural Network From Scratch in Python | Machine Learning Tutorial (Step-by-Step)
In this video, you’ll learn how to build a neural network from scratch using Python and NumPy — no TensorFlow, no PyTorch, just pure code and logic! 🚀
We’ll cover everything you need to understand the core of deep learning:
✅ What is a Neural Network?
✅ Forward Propagation Explained
✅ Activation Functions (ReLU, Sigmoid, etc.)
✅ Loss Function and Backpropagation
✅ Gradient Descent Optimization
✅ Hands-on Implementation Using Python & NumPy
By the end of this tutorial, you’ll have a fully working neural network model that learns from data — built completely from scratch!
📚 Topics Covered:
Neural Network Basics
Math Behind Deep Learning
Step-by-Step Python Implementation
How Backpropagation Works
Build Your Own AI Model
💻 Resources:
👉 GitHub Code: [Add your link here]
👉 Colab Notebook: [Add your link here]
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