Backpropagation Visually Explained | Deep Learning Part 2

ByteQuest · Beginner ·📐 ML Fundamentals ·9mo ago

About this lesson

in this video we go deep into backpropagation and see how neural networks actually learn. first we look at a super simple network with one hidden neuron and then move step by step into bigger ones. we talk about forward pass, loss function, gradient descent, chain rule and how weights + biases get updated. by the end you’ll get the full picture of how training works in neural nets. timestamps: 0:00 Intro 0: 30 simple network setup 5:40 General Neural Nework Case 12:00 Loss Function Links of related videos:- Neural Networks:- https://youtu.be/sE6OaMndGZg Gradient Descent :- https://youtu.be/2xdUsy3oq-4 Chain Rule (3b1b):- https://youtu.be/YG15m2VwSjA If you're passionate about learning complex concepts in the simplest way possible, you're in the right place. I create visual explanations using animations to make topics more intuitive and engaging—especially in Algorithms, AI, machine learning, and beyond. 🎥 Animations created using Manim: Manim is an open-source Python library for creating mathematical animations. Learn more or try it yourself: 🔗 https://www.manim.community Let's Connect:- GitHub:- https://github.com/ByteQuest0 Reddit:- https://www.reddit.com/r/ByteQuest/

Original Description

in this video we go deep into backpropagation and see how neural networks actually learn. first we look at a super simple network with one hidden neuron and then move step by step into bigger ones. we talk about forward pass, loss function, gradient descent, chain rule and how weights + biases get updated. by the end you’ll get the full picture of how training works in neural nets. timestamps: 0:00 Intro 0: 30 simple network setup 5:40 General Neural Nework Case 12:00 Loss Function Links of related videos:- Neural Networks:- https://youtu.be/sE6OaMndGZg Gradient Descent :- https://youtu.be/2xdUsy3oq-4 Chain Rule (3b1b):- https://youtu.be/YG15m2VwSjA If you're passionate about learning complex concepts in the simplest way possible, you're in the right place. I create visual explanations using animations to make topics more intuitive and engaging—especially in Algorithms, AI, machine learning, and beyond. 🎥 Animations created using Manim: Manim is an open-source Python library for creating mathematical animations. Learn more or try it yourself: 🔗 https://www.manim.community Let's Connect:- GitHub:- https://github.com/ByteQuest0 Reddit:- https://www.reddit.com/r/ByteQuest/

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Chapters (3)

Intro

5:40 General Neural Nework Case

12:00 Loss Function

Dropout in Deep Learning