Скачать или смотреть How AI Learns Using Backpropagation | Neural Network Learning Explained

🧠 Backpropagation is the core learning mechanism of Deep Learning.
It’s how neural networks correct their mistakes and improve accuracy — just like how humans learn from feedback.

In this visually explained video, you will understand:

🔹 What is Backpropagation (simple definition)
🔹 How error moves backward in a neural network
🔹 How weights get updated using Gradient Descent
🔹 Forward pass vs backward pass (clear difference)
🔹 Why backpropagation is used in ChatGPT, CNN, LSTM, BERT, GPT, Transformers

🔍 Learning Flow Covered in Video:

📌 Input Data
📌 Forward Pass — Model makes prediction
📌 Compare with real value
📌 Calculate Error (Loss)
📌 Backpropagation — Send error backward
📌 Update Weights — Gradient Descent
📌 Better Prediction → Repeat until accurate

🎯 Who should watch this?

✔ AI & ML beginners
✔ B.Tech, MCA, Data Science students
✔ Those preparing for ML interviews
✔ Anyone trying to understand how AI learns