Deep Learning with TensorFlow (Paperback)
暫譯: 使用 TensorFlow 的深度學習 (平裝本)
Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy
- 出版商: Packt Publishing
- 出版日期: 2017-04-24
- 定價: $1,650
- 售價: 6.0 折 $990
- 語言: 英文
- 頁數: 320
- 裝訂: Paperback
- ISBN: 1786469782
- ISBN-13: 9781786469786
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相關分類:
TensorFlow
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相關翻譯:
TensorFlow深度學習 (簡中版)
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相關主題
商品描述
Key Features
- Learn advanced techniques in deep learning with this example-rich guide on Google's brainchild
- Explore various neural networks with the help of this comprehensive guide
- Advanced guide on machine learning techniques, in particular TensorFlow for deep learning.
Book Description
Deep learning is the next step after machine learning. It is machine learning but with a more advanced implementation. As machine learning is no longer an academic topic, but a mainstream practice, deep learning has taken a front seat. With deep learning being used by many data scientists, deeper neural networks are evaluated for accurate results. Data scientists want to explore data abstraction layers and this book will be their guide on this journey. This book evaluates common, and not so common, deep neural networks and shows how these can be exploited in the real world with complex raw data using TensorFlow.
The book will take you through an understanding of the current machine learning landscape then delve into TensorFlow and how to use it by considering various data sets and use cases. Throughout the chapters, you'll learn how to implement various deep learning algorithms for your machine learning systems and integrate them into your product offerings such as search, image recognition, and language processing. Additionally, we'll examine its performance by optimizing it with respect to its various parameters, comparing it against benchmarks along with teaching machines to learn from the information and determine the ideal behavior within a specific context, in order to maximize its performance.
After finishing the book, you will be familiar with machine learning techniques, in particular TensorFlow for deep learning, and will be ready to apply some of your knowledge in a real project either in a research or commercial setting.
What you will learn
- Provide an overview of the machine learning landscape
- Look at the historical development and progress of deep learning
- Describe TensorFlow and become very familiar with it both in theory and in practice
- Access public datasets and use TF to load, process, clean, and transform data
- Use TensorFlow on real-world data sets including images and text
- Get familiar with TensorFlow by applying it in various hands on exercises using the command line
- Evaluate the performance of your deep learning models
- Quickly teach machines to learn from data by exploring reinforcement learning techniques.
- Understand how this technology is being used in the real world by exploring active areas of deep learning research and application.
商品描述(中文翻譯)
主要特點
- 透過這本充滿範例的指南,學習深度學習的進階技術,專注於Google的創新。
- 利用這本全面的指南,探索各種神經網絡。
- 進階的機器學習技術指南,特別是針對深度學習的TensorFlow。
書籍描述
深度學習是機器學習之後的下一步。它是機器學習,但實現上更為先進。隨著機器學習不再僅僅是學術主題,而成為主流實踐,深度學習已經成為焦點。許多數據科學家正在使用深度學習,並評估更深的神經網絡以獲得準確的結果。數據科學家希望探索數據抽象層,而這本書將成為他們在這段旅程中的指南。本書評估了常見和不常見的深度神經網絡,並展示如何利用TensorFlow在現實世界中處理複雜的原始數據。
本書將引導您了解當前的機器學習環境,然後深入探討TensorFlow及其使用方法,考慮各種數據集和使用案例。在各章中,您將學習如何為您的機器學習系統實現各種深度學習算法,並將其整合到您的產品中,例如搜索、圖像識別和語言處理。此外,我們將通過優化其各種參數來檢查其性能,並將其與基準進行比較,教導機器從信息中學習並確定在特定上下文中的理想行為,以最大化其性能。
完成本書後,您將熟悉機器學習技術,特別是針對深度學習的TensorFlow,並準備在研究或商業環境中將您的知識應用於實際項目中。
您將學到的內容
- 提供機器學習環境的概述
- 了解深度學習的歷史發展和進展
- 描述TensorFlow,並在理論和實踐中非常熟悉它
- 訪問公共數據集,並使用TF加載、處理、清理和轉換數據
- 在現實世界的數據集上使用TensorFlow,包括圖像和文本
- 通過使用命令行進行各種實作練習,熟悉TensorFlow
- 評估您的深度學習模型的性能
- 通過探索強化學習技術,快速教導機器從數據中學習
- 通過探索深度學習研究和應用的活躍領域,了解這項技術在現實世界中的應用。




























