What's New in TensorFlow 2.0

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: $1,240
  • 貴賓價: 9.5 折 $1,178
  • 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 2.0 新特性》是一本關於 TensorFlow 2.0 的書籍，它是一個端到端的機器學習平台，適用於專家和初學者，並且在 TensorFlow 2.0 中改進了其簡單性和易用性。本書將幫助您了解並利用最新的 TensorFlow 功能。

《TensorFlow 2.0 新特性》首先聚焦於高級概念，如新的 TensorFlow Keras API、即時執行和高效的分佈策略，這些策略可以幫助您在多個 GPU 和 TPU 上運行機器學習模型。接著，本書將引導您完成數據輸入和訓練流程的構建，並提供使用新的 tf.keras API 創建模型時的建議和最佳實踐。您將探索使用 TF Serving 和其他多平台部署來構建推理流程，然後深入研究新發布的 AIY，這實際上是一個自助式人工智能。本書深入介紹核心 API，幫助您構建統一的卷積和循環層，並使用 TensorBoard 進行深度學習模型的可視化和假設分析。

通過閱讀本書，您將了解 TF 2.0 和 TF 1.x 之間的兼容性，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在深度學習電子製造中心擔任主任，負責在半導體和電子製造行業中研究和開發基於TensorFlow的深度學習應用。他的職責之一是教授和培訓專業人士深度學習技術。他在軟體工程和管理方面有豐富的經驗，並對深度學習產生了濃厚的興趣。他轉向自然語言理解（NLU），在Abzooba進一步追求深度學習，並為金融行業建立了一個信息檢索系統。他還曾在Ansys Inc.擔任高級經理（工程）和技術專家（數據科學），並引入了多個機器學習應用。

Alizishaan Khatri
Alizishaan Khatri在矽谷擔任機器學習工程師。他使用TensorFlow構建、設計和維護使用深度學習進行自然語言處理應用的生產級系統。他建立的一個重要系統是基於深度學習的聊天內容辱罵檢測系統。他還為不同的用例開發了文本分類和命名實體識別（NER）系統。他熱衷於與社區分享想法，並經常在全球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。他的論文提出了解決深度學習中過度擬合問題的解決方案。在工作之外，他喜歡滑雪和登山。

Tanish Baranwal
Tanish Baranwal是一名高中二年級學生，與家人一起住在加利福尼亞州，過去3年他與父親一起使用TensorFlow進行深度學習項目。他從一年級開始編程已有9年的經驗，精通Python和JavaScript，現在正在學習C++。他擁有來自各種在線課程的證書，並在學校贏得了創業展示獎。他的一些深度學習項目包括用於交易欺詐的異常檢測系統，一個在不使用時關閉家用熱水器以節省能源的系統，以及一個完全功能的風格轉換程序，可以將任何照片以另一種風格重新創建。他還在Medium上撰寫了關於深度學習的博客，瀏覽量超過1,000次。

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