| 1 - Introduction.mp4 | 11.5 MB | ||
| 10 - Profiling the Model Theory.mp4 | 10 MB | ||
| 11 - Profiling the Model Practical.mp4 | 93.5 MB | ||
| 12 - Inference.mp4 | 89.5 MB | ||
| 13 - Downloading the Model.mp4 | 83.3 MB | ||
| 14 - Introduction to Quantization.mp4 | 15.6 MB | ||
| 15 - Symmetrics quantization.mp4 | 24.8 MB | ||
| 16 - Asymmetrics Quantization.mp4 | 29.8 MB | ||
| 17 - Quantization Techniques Practical Application.mp4 | 80.3 MB | ||
| 18 - About your certificate.html | 921.6 B | ||
| 19 - Bonus lecture.html | 6.3 KB | ||
| 2 - OnDevice Introduction.mp4 | 13.4 MB | ||
| 3 - Qualcomm AI Hub Introduction.mp4 | 25.5 MB | ||
| 4 - Qualcomm AI Hub Login.mp4 | 19.2 MB | ||
| 5 - Steps for OnDevice Deployment.mp4 | 17.9 MB | ||
| 6 - Model Training Phase Theory.mp4 | 21.3 MB | ||
| 7 - Training the Model Practical.mp4 | 41 MB | ||
| 8 - Compiling the Model Theory.mp4 | 45.9 MB | ||
| 9 - Compiling the Model Practical.mp4 | 42 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 21 total files | |||
Build On-Device Ai
https://WebToolTip.com
Published 2/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 664.48 MB | Duration: 1h 54m
Master On-Device AI! Learn to Train, Compile and Profile AI Models for Edge Device deployement with Qualcomm AI Hub
What you'll learn
Understand the complete workflow of On-Device AI deployment, from training to inference
Learn how to use Qualcomm AI Hub for managing, compiling, and optimizing AI models
Master model profiling and compilation to enhance performance on edge devices
Learn quantization techniques to optimize AI models for mobile, IoT, and embedded systems
Understand the difference between symmetric and asymmetric quantization
Requirements
Basic Python knowledge is recommended, but no prior AI experience is required
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