Deep Learning with Swift for TensorFlow (1st Edition)

Differentiable Programming with Swift

Deep Learning with Swift for TensorFlow (1st Edition)
Rahul Bhalley
RRP:
NZ$ 94.99
Our Price:
NZ$ 75.99
Paperback
h235 x 155mm - 470pg
11 Jan 2021 US
International import eta 7-19 days
9781484263297
Out Of Stock
Currently no stock in-store, stock is sourced to your order
Discover more insight about deep learning and how to work with Swift for TensorFlow to develop intelligent apps. TensorFlow was designed for easy adoption by iOS programmers working in Swift. This book covers the established and tested concepts and ties them to modern Swift programming and applicable use in developing for iOS. Using illustrative examples, the book starts off by introducing you to basic machine learning concepts along with code snippets in Swift for TensorFlow. . Fundamentals of neural networks required to understand today' s deep learning research will be covered and put in the context of working in the Swift language with the goal of developing primarily for Apple' s mobile ecosystem. Other important topics covered include computation graphs, loss functions, optimization techniques, regulazrizing nueral networks, recurrent neural networks-such as those used in Siri and Google Translate; and convolutional neural networks. You' ll also learn to reuse pre-trained neural networks and work with generative models. Finally, developing and building in security to models is addressed. Swift code will be provided throughout the book to keep the concepts grounded in application within Apple' s frameworks. What You' ll Learn * Write machine learning code in Swift * Run neural networks in Apple environments * Apply fundamental deep learning concepts to mobile app development Who This Book Is For Programmers familiar with Swift and the basics of AI
Rahul Bhalley published the first research paper on machine learning in 2016 for an IEEE conference. He actively contributes to open-source works on GitHub, including contributing to others' repositories and writing his own neural networks for generating images. He also focuses on generative models-especially Generative Adversarial Networks and published on the subject in February 2019 with CycleGAN-QP for artist style transfer. He has also worked with Apple' s Swift and shares Google' s vision of making it easy for others to understand deep learning with Swift.
Status: No local stock, title imported to order
ISBN-13: 9781484263297
Published: 11 Jan 2021
Published In: United States
Imprint: APress
Publisher: APress
Format: Paperback
Height: 235mm
Width: 155mm
Pages: 470

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