What this book covers

Chapter 1, Deep Neural Networks - Overview, it gives a quick refresher of the science of deep neural networks and different frameworks that can be used to implement such networks, with the mathematics behind them.

Chapter 2, Introduction to Convolutional Neural Networks, it introduces the readers to convolutional neural networks and shows how deep learning can be used to extract insights from images.

Chapter 3, Build Your First CNN and Performance Optimization, constructs a simple CNN model for image classification from scratch, and explains how to tune hyperparameters and optimize training time and performance of CNNs for improved efficiency and accuracy respectively.

Chapter 4, Popular CNN Model Architectures, shows ...

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