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- Sep 4, 2023
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137.86 MB | 00:03:53 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
01 - Getting started with TinyML.mp4 (2.88 MB)
02 - What is TinyML.mp4 (8.28 MB)
03 - What you should know.mp4 (3.15 MB)
01 - Defining constraints.mp4 (4.29 MB)
02 - Checklist for a TinyML problem.mp4 (7.71 MB)
01 - Pre-trained models.mp4 (8.32 MB)
02 - Quantization and types of quantization.mp4 (7.6 MB)
03 - TFLite post training quantization.mp4 (8.88 MB)
04 - Quantization awareness training in TFLite.mp4 (6.95 MB)
05 - Pruning.mp4 (8.47 MB)
06 - Knowledge distillation.mp4 (6.08 MB)
07 - Challenge Compare results of optimization.mp4 (8.19 MB)
08 - Solution Compare results of optimization.mp4 (11.54 MB)
01 - Edge impulse.mp4 (3.93 MB)
02 - Deploy a classification project to your phone.mp4 (5.21 MB)
03 - Challenge Deploy a regression model to your phone.mp4 (1.95 MB)
04 - Solution Deploy a regression model to your phone.mp4 (6.47 MB)
01 - Hardware devices.mp4 (8.38 MB)
02 - Bringing all the concepts together.mp4 (6.6 MB)
01 - Resources for TinyML.mp4 (5.26 MB)
02 - Future of the TinyML Research directions.mp4 (6.33 MB)
03 - Next steps with TinyML.mp4 (1.18 MB)]
Screenshot
Code:
https://rapidgator.net/file/1ed0515ed3a1561b07fddab264cedc8b/LinkedIn.-.Learning.TinyML.A.Hands-On.Course.rar
Code:
https://nitroflare.com/view/96B8D08A5A5BB21/LinkedIn.-.Learning.TinyML.A.Hands-On.Course.rar
Code:
https://turbobit.net/imfg2r9w8c8o/LinkedIn.-.Learning.TinyML.A.Hands-On.Course.rar.html