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Pe YEO găsești Hands-On Computer Vision with TensorFlow de la Benjamin Planche, în categoria Computers.
Indiferent de nevoile tale, Hands-On Computer Vision with TensorFlow 2: Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras - Benjamin Planche din categoria Computers îți poate aduce un echilibru perfect între calitate și preț, cu avantaje practice și moderne.
Preț: 157.45 Lei
Caracteristicile produsului Hands-On Computer Vision with TensorFlow
- Brand: Benjamin Planche
- Categoria: Computers
- Magazin: libris.ro
- Ultima actualizare: 02-11-2024 01:25:46
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Descriere magazin:
A practical guide to building high performance systems for object detection, segmentation, video
processing, smartphone applications, and more Key Features Discover how to build, train, and serve your own
deep neural networks
with TensorFlow 2 and
Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Learn how to run your models on mobile devices and web pages and improve their performance Book Description
Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore
TensorFlow 2, the brand new version of Google\'s open source framework for machine
learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks.
Hands-On
Computer Vision with TensorFlow 2 starts
with the fundamentals of computer vision and
deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive
Keras interface. You\'ll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to
create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer
learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learn Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application\'s performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser