What's New in TensorFlow 2.0
暫譯: TensorFlow 2.0 新特性解析

Baranwal, Ajay, Khatri, Alizishaan, Baranwal, Tanish

What's New in TensorFlow 2.0
  • 出版商: Packt Publishing
  • 出版日期: 2019-08-09
  • 售價: $1,250
  • 貴賓價: 9.5 折 $1,188
  • 語言: 英文
  • 頁數: 202
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1838823859
  • ISBN-13: 9781838823856
  • 相關分類: DeepLearning、TensorFlow

    • 海外代購書籍(需單獨結帳)

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商品描述

TensorFlow is an end-to-end machine learning platform for experts as well as beginners, and its new version, TensorFlow 2.0 (TF 2.0), improves its simplicity and ease of use. This book will help you understand and utilize the latest TensorFlow features.

 

What's New in TensorFlow 2.0 starts by focusing on advanced concepts such as the new TensorFlow Keras APIs, eager execution, and efficient distribution strategies that help you to run your machine learning models on multiple GPUs and TPUs. The book then takes you through the process of building data ingestion and training pipelines, and it provides recommendations and best practices for feeding data to models created using the new tf.keras API. You'll explore the process of building an inference pipeline using TF Serving and other multi-platform deployments before moving on to explore the newly released AIY, which is essentially do-it-yourself AI. This book delves into the core APIs to help you build unified convolutional and recurrent layers and use TensorBoard to visualize deep learning models using what-if analysis.

 

By the end of the book, you'll have learned about compatibility between TF 2.0 and TF 1.x and be able to migrate to TF 2.0 smoothly.

商品描述(中文翻譯)




TensorFlow 是一個適合專家和初學者的端到端機器學習平台，其新版本 TensorFlow 2.0 (TF 2.0) 提升了簡單性和易用性。本書將幫助您理解和利用最新的 TensorFlow 功能。

 

TensorFlow 2.0 的新特性首先專注於高級概念，例如新的 TensorFlow Keras API、即時執行以及有效的分佈策略，這些都能幫助您在多個 GPU 和 TPU 上運行機器學習模型。本書接著帶您了解構建數據攝取和訓練管道的過程，並提供使用新的 tf.keras API 為模型提供數據的建議和最佳實踐。您將探索使用 TF Serving 和其他多平台部署構建推理管道的過程，然後再深入了解新發布的 AIY，這基本上是自助式 AI。本書深入探討核心 API，幫助您構建統一的卷積層和循環層，並使用 TensorBoard 進行深度學習模型的可視化，透過假設分析來進行探索。

 

在本書結束時，您將了解 TF 2.0 與 TF 1.x 之間的相容性，並能夠順利遷移到 TF 2.0。




作者簡介

Ajay Baranwal

Ajay Baranwal works as a director at the Center for Deep Learning in Electronics Manufacturing, where he is responsible for researching and developing TensorFlow-based deep learning applications in the semiconductor and electronics manufacturing industry. Part of his role is to teach and train deep learning techniques to professionals. He has a solid history of software engineering and management, where he got hooked on deep learning. He moved to natural language understanding (NLU) to pursue deep learning further at Abzooba and built an information retrieval system for the finance sector. He has also worked at Ansys Inc. as a senior manager (engineering) and a technical fellow (data science) and introduced several ML applications.

Alizishaan Khatri

Alizishaan Khatri works as a machine learning engineer in Silicon Valley. He uses TensorFlow to build, design, and maintain production-grade systems that use deep learning for NLP applications. A major system he has built is a deep learning-based system for detecting offensive content in chats. Other works he has done includes text classification and named entity recognition (NER) systems for different use cases. He is passionate about sharing ideas with the community and frequently speaks at tech conferences across the globe. He holds a master's degree in computer science from the SUNY Buffalo University. His thesis proposed a solution to the problem of overfitting in deep learning. Outside of his work, he enjoys skiing and mountaineering.

Tanish Baranwal

Tanish Baranwal is a sophomore in high school and lives in California with his family and has worked with his dad on deep learning projects using TensorFlow for the last 3 years. He has been coding for 9 years (since 1st grade) and is well versed in Python and JavaScript. He is now learning C++. He has certificates from various online courses and has won the Entrepreneurship Showcase Award at his school. Some of his deep learning projects include anomaly detection systems for transaction fraud, a system to save energy by turning off domestic water heaters when not in use, and a fully functional style transfer program that can recreate any photograph in another style. He has also written blogs on deep learning on Medium with over 1,000 views.

作者簡介(中文翻譯)

Ajay Baranwal

Ajay Baranwal 擔任電子製造深度學習中心的主任，負責研究和開發基於 TensorFlow 的深度學習應用於半導體和電子製造行業。他的工作之一是教授和訓練專業人士深度學習技術。他擁有堅實的軟體工程和管理背景，並因此對深度學習產生濃厚興趣。他轉向自然語言理解（NLU），在 Abzooba 深入探索深度學習，並為金融行業建立了一個資訊檢索系統。他還曾在 Ansys Inc. 擔任高級經理（工程）和技術研究員（數據科學），並引入了幾個機器學習應用。

Alizishaan Khatri

Alizishaan Khatri 在矽谷擔任機器學習工程師。他使用 TensorFlow 建立、設計和維護生產級系統，這些系統利用深度學習進行自然語言處理應用。他所建立的一個主要系統是基於深度學習的聊天內容攻擊性檢測系統。他的其他工作包括針對不同用例的文本分類和命名實體識別（NER）系統。他熱衷於與社群分享想法，並經常在全球各地的技術會議上發表演講。他擁有紐約州立大學水牛城分校的計算機科學碩士學位，論文提出了解決深度學習過擬合問題的方案。在工作之餘，他喜歡滑雪和登山。

Tanish Baranwal

Tanish Baranwal 是一名高中二年級學生，與家人住在加州，過去三年來一直與父親合作使用 TensorFlow 進行深度學習項目。他從小學一年級開始編程，至今已有九年經驗，精通 Python 和 JavaScript，現在正在學習 C++。他擁有多個線上課程的證書，並在學校獲得了創業展示獎。他的一些深度學習項目包括用於交易詐騙的異常檢測系統、一個在不使用時關閉家庭熱水器以節省能源的系統，以及一個能夠將任何照片轉換為另一種風格的完整功能風格轉換程序。他還在 Medium 上撰寫了有關深度學習的博客，獲得了超過 1,000 次的瀏覽。

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