Explore a novel method for compressing convolutional neural networks (CNNs) in this 31-minute tinyML Talk by Ehsan Saboori from Deeplite. Discover the "network within a network" paradigm, designed to preserve maximum accuracy while meeting strict constraints on model size for ultra-low power and low-latency deep learning models on edge devices. Learn about the automated approach to approximating individual layers within neural networks using smaller networks, and understand its implications for tinyML applications. Gain insights into the VGG architecture, transformation functions, and experimental results. Conclude with a Q&A session to deepen your understanding of this innovative CNN design space exploration for resource-limited devices.