| 书目名称 | State-of-the-Art Deep Learning Models in TensorFlow | | 副标题 | Modern Machine Learn | | 编辑 | David Paper | | 视频video | | | 概述 | Covers state-of-the-art deep learning models that are needed for success in the field.Leverages Google’s TensorFlow-Colab Ecosystem for executing learning model applications in Python.Provides example | | 图书封面 |  | | 描述 | .Use TensorFlow 2.x in the Google Colab ecosystem to create state-of-the-art deep learning models guided by hands-on examples. The Colab ecosystem provides a free cloud service with easy access to on-demand GPU (and TPU) hardware acceleration for fast execution of the models you learn to build. This book teaches you state-of-the-art deep learning models in an applied manner with the only requirement being an Internet connection. The Colab ecosystem provides everything else that you need, including Python, TensorFlow 2.x, GPU and TPU support, and Jupyter Notebooks...The book begins with an example-driven approach to building input pipelines that feed all machine learning models. You will learn how to provision a workspace on the Colab ecosystem to enable construction of effective input pipelines in a step-by-step manner. From there, you will progress into data augmentation techniques and TensorFlow datasets to gain a deeper understanding of how to work with complex datasets. You will find coverage of Tensor Processing Units (TPUs) and transfer learning followed by state-of-the-art deep learning models, including autoencoders, generative adversarial networks, fast style transfer, obj | | 出版日期 | Book 2021 | | 关键词 | Google Colab; Colaboratory Cloud; TensorFlow 2; x; Deep Learning Models; Tensors; tf; data API; tf; data Data | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-7341-8 | | isbn_softcover | 978-1-4842-7340-1 | | isbn_ebook | 978-1-4842-7341-8 | | copyright | David Paper 2021 |
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发表于 2025-3-21 18:59:53
