This section familiarizes the reader with different types of convolutional and pooling layers that may be used in neural networks to process sensory input, from images on your laptop, to databases and real-time IoT applications. Readers will learn about using pretrained models, such as LeNet, and partial convolutional networks for image and video reconstruction on Keras, gain insights into how to deploy models using REST APIs, and then embed them in Raspberry computing devices for custom use cases, such as photography, surveillance, and inventory management.
Readers will be exposed to the underlying architectures of reinforcement learning networks in detail and learn how to implement core and extended layers in Keras for desired outcomes.
Then, they will dive deeper into the theory behind different types of recurrent networks and...
