Convolutional Neural Networks with Swift for Tensorflow : Image Recognition and Dataset Categorization

Dive into and apply practical machine learning and dataset categorization techniques while learning Tensorflow and deep learning. This book uses convolutional neural networks to do image recognition all in the familiar and easy to work with Swift language. It begins with a basic machine learning overview and then ramps up to neural networks and convolutions and how they work. Using Swift and Tensorflow, you'll perform data augmentation, build and train large networks, and build networks for mobile devices. You’ll also cover cloud training and the network you build can categorize greyscale data, such as mnist, to large scale modern approaches that can categorize large datasets, such as imagenet. Convolutional Neural Networks with Swift for Tensorflow uses a simple approach that adds progressive layers of complexity until you have arrived at the current state of the art for this field. What You'll Learn Categorize and augment datasets Build and train large networks, including via cloud solutions Deploy complex systems to mobile devices Who This Book Is For Developers with Swift programming experience who would like to learn convolutional neural networks by example using Swift for Tensorflow as a starting point. Formulata da Albert Einstein con qualche con­tributo da parte di amici e colleghi tra il 1907 e il 1917, la relatività generale è la teoria che og­gi meglio descrive lo spazio, il tempo e la gravi­tà. Con la chiarezza espositiva che lo ha reso ce­lebre in tutto il mondo, Rovelli ne illustra i fon­damenti fisici, filosofici e matematici, ne presen­ta la struttura formale, e ne deriva nel modo più semplice le sue stupefacenti predizioni – buchi neri, onde gravitazionali, espansione dell'uni­verso, dilatazione del tempo... –, senza trascu­rare alcune idee di base su come potrebbe es­sere estesa ai fenomeni quantistici. Per il letto­re con formazione scientifica questo libro rap­presenterà dunque una agile introduzione agli aspetti fondamentali della teoria, ma nel con­tempo lo scienziato e lo studente avanzato vi tro­veranno una discussione approfondita e origi­nale della sua struttura concettuale. Nel secolo scorso la relatività generale ha rivo­luzionato la fisica, ma è con le applicazioni e le osservazioni degli ultimi anni, coronate da nu­merosi premi Nobel, che sono esplose e diven­tate evidenti la sua vitalità e fecondità: Rovelli descrive questi risultati recenti, guidando così il lettore ad apprezzare «la scintillante bellezza e la semplicità delle idee su cui essa si basa». Dive into and apply practical machine learning and dataset categorization techniques while learning Tensorflow and deep learning. This book uses convolutional neural networks to do image recognition all in the familiar and easy to work with Swift language. It begins with a basic machine learning overview and then ramps up to neural networks and convolutions and how they work. Using Swift and Tensorflow, you'll perform data augmentation, build and train large networks, and build networks for mobile devices. You'll also cover cloud training and the network you build can categorize greyscale data, such as mnist, to large scale modern approaches that can categorize large datasets, such as imagenet. Convolutional Neural Networks with Swift for Tensorflow uses a simple approach that adds progressive layers of complexity until you have arrived at the current state of the art for this field. You will: Categorize and augment datasets Build and train large networks, including via cloud solutions Deploy complex systems to mobile devices