Neural Network Quantization Unpacked

This chapter explores the complexities of neural network quantization and its role in automating deep learning processes. It discusses advancements in techniques that enhance model efficiency while addressing challenges such as setting quantization ranges and avoiding biases. The chapter also highlights a novel data-free quantization approach, demonstrating significant performance gains across various neural architectures.