#dl 14 Understanding CNNs & LeNet-5 | Beginner-Friendly Deep Dive with Visuals & Math

In this lecture, we break down Convolutional Neural Networks (CNNs) in a simple, visual, and beginner-friendly way — perfect for students, machine learning enthusiasts, and anyone curious about how computers learn to "see".

📌 What You’ll Learn:
Intro: What are CNNs, and why are they important in deep learning?
How Convolution Filters Work: Watch filters detect edges, shapes, and complex features across layers.

Max-Pooling Explained Visually: Understand how spatial dimensions shrink while key features remain.

Full LeNet-5 Architecture Breakdown:

Layer-by-layer explanation

Filter sizes, strides, padding, channels

Illustrated step-through of the network

Parameter Calculations (On-Screen Math):

🔢 Conv layers

🔢 Max-pooling layers

🔢 Fully connected layers

Data Flow Explained: How raw pixels transform into meaningful predictions.

🎯

Machine learning beginners

Students exploring deep learning

Anyone curious about image recognition models

✅ Diagrams and animations included
✅ On-screen calculations
✅ No coding required

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#CNN #LeNet5 #DeepLearning #MachineLearning #AIExplained #VisualLearning #BeginnerAI

Видео #dl 14 Understanding CNNs & LeNet-5 | Beginner-Friendly Deep Dive with Visuals & Math канала Ranjeet Ranjan Jha

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19 октября 2025 г. 15:55:21

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Ranjeet Ranjan Jha

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