P2.3.7.1 How CNN Actually Works — Convolution, Pooling, Flatten & Two Pipelines Explained

Description:
Before writing a single line of CNN code — you need to understand what's actually happening inside.

In this video we cover the complete CNN theory from scratch:

• Why ANN fails on images — and what CNN does differently
• Convolution — how filters slide across an image and detect patterns
• Pooling — shrinking feature maps while keeping what matters
• Flatten — the bridge from 2D feature maps to Dense layers
• Classification Pipeline — full end-to-end flow from image to label
• Object Detection Pipeline — same backbone, completely different head
• Key terms demystified: Bounding Box, Anchor Boxes, Confidence Score, Non-Max Suppression (NMS)

No code in this video — just the concepts, clearly explained with diagrams and pipelines.
The code comes in the next 3 videos.


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???? Part of the GenAI Foundation Course
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???? GitHub: https://github.com/MaighaInc/pycore/tree/main/Course-GenAIFoundation/P2_LegacyToGenAI/P2.3_DL_Foundations
???? Discord: https://discord.com/invite/V35dKcApS6

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