Quantization in deep learning | Deep Learning Tutorial 49 (Tensorflow, Keras & Python)

Are you planning to deploy a deep learning model on any edge device (microcontrollers, cell phone or wearable device)? You need to optimize or downsize your huge model so that you can run the model efficiently in low resource environment. Quantization is the technique that let’s you do that. In this video we will cover topics outlined below,

⭐️ Timestamps ⭐️
00:00 Overview
01:03 What is Quantization?
03:49 Two ways to perform Quantization
03:56 Post training Quantization
04:47 Quantization aware training
05:47 Coding

Code: https://github.com/codebasics/deep-learning-keras-tf-tutorial/blob/master/49_quantization/quantization.ipynb

Tensorflow articles on quantization: https://www.tensorflow.org/model_optimization/guide/quantization/training
https://www.tensorflow.org/model_optimization/guide/quantization/post_training
https://blog.tensorflow.org/2020/04/quantization-aware-training-with-tensorflow-model-optimization-toolkit.html

Deep learning playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu7CxAacxVndI4bE_o3BDtO
Machine learning playlist : https://www.youtube.com/playlist?list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw  
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#quantization #quantizationtensorflow #quantizationneuralnetwork #quantizationdeeplearning #tflitequantization #tflitequantizationawaretraining #tensorflowquantizationtutorial

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