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✂️ Topic 41: Quantization & Pruning for Deployment

Course: AI Infrastructure — Section 5: Model Serving & Inference Topic: 41 of 70 | Prev:…

Overview
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✂️ Topic 41: Quantization & Pruning for Deployment — Quick Facts

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Prev: [40-ONNX-TensorRT.md](40-ONNX-TensorRT.md): Next: 42-Batching-Caching.md

Topic 1
📥 📥 🧠 🔬 💡 🎯

🎯 Overview

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Quantization = model weights ko…

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Pruning = unnecessary…

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Knowledge Distillation = big model…

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Goal: Model ko chhota + fast…

Topic 2
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🔄 Model Compression Techniques

💡 ` ┌──────────────────────────────────────────────────────────────┐ │ MODEL COMPRESSION…
Topic 3
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🐍 Complete Python Implementation

🎯 `python ============================================================ Quantization &…
Topic 4
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📊 When to Use What

⭐ | Technique | Best For | Speedup | Accuracy Loss |…
Topic 5
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❓ Quiz — 5 MCQs

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A) 2x

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B) 4x — 32 bits → 8 bits = 4x…

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C) 8x

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D) Same size

Topic 6
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🔗 Navigation

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Quiz — Question 1

✂️ Topic 41: Quantization & Pruning for Deployment ka sabse sahi definition kya hai?

Complete! 🎉
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✂️ Topic 41: Quantization & Pruning for Deployment Complete!

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✂️ Topic 41: Quantization & Pruning for Deployment Complete

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