Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python

Jojo Moolayil

  • 出版商: Apress
  • 出版日期: 2018-12-07
  • 售價: $1,575
  • 貴賓價: 9.5$1,496
  • 語言: 英文
  • 頁數: 182
  • 裝訂: Paperback
  • ISBN: 1484242394
  • ISBN-13: 9781484242391
  • 相關分類: DeepLearningPython程式語言
  • 立即出貨 (庫存 < 4)

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商品描述

 

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.

The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You’ll tackle one use case for regression and another for classification leveraging popular Kaggle datasets.

Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you’ll further hone your skills in deep learning and cover areas of active development and research in deep learning. 

At the end of Learn Keras for Deep Neural Networks, you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras.

What You’ll Learn

  • Master fast-paced practical deep learning concepts with math- and programming-friendly abstractions.
  • Design, develop, train, validate, and deploy deep neural networks using the Keras framework
  • Use best practices for debugging and validating deep learning models
  • Deploy and integrate deep learning as a service into a larger software service or product
  • Extend deep learning principles into other popular frameworks

Who This Book Is For 

Software engineers and data engineers with basic programming skills in any language and who are keen on exploring deep learning for a career move or an enterprise project.

 

 

 

 

商品描述(中文翻譯)

學習使用Keras和Python以數學和程式設計友好的方式來理解和實現深度神經網絡。本書著重於以端到端的方式開發基於Keras的監督學習演算法,並實現在實際業務中的使用案例。

整本書分為三個部分,每個部分有兩章。第一部分為您提供了所有必要的基礎知識,讓您能夠開始進行深度學習。第1章介紹了深度學習的世界及其與機器學習的區別,深度學習的框架選擇以及Keras生態系統。您將解決一個實際的業務問題,該問題可以通過使用深度神經網絡的監督學習演算法來解決。您將使用流行的Kaggle數據集來處理一個回歸問題和一個分類問題。

接下來,您將看到深度學習中一個有趣且具有挑戰性的部分:超參數調整;這將幫助您在構建強大的深度學習應用程序時進一步改進模型。最後,您將進一步提升深度學習技能,並涵蓋深度學習中正在積極發展和研究的領域。

在《深度神經網絡的Keras學習》結束時,您將對深度學習原理有全面的理解,並具有在Keras中開發企業級深度學習解決方案的實際經驗。

您將學到什麼:

- 以數學和程式設計友好的抽象方式掌握快節奏的實用深度學習概念。
- 使用Keras框架設計、開發、訓練、驗證和部署深度神經網絡。
- 使用最佳實踐來調試和驗證深度學習模型。
- 將深度學習作為服務部署和集成到更大的軟件服務或產品中。
- 在其他流行框架中擴展深度學習原理。

本書適合對任何語言具有基本程式設計技能的軟件工程師和數據工程師,他們有興趣探索深度學習以進行職業轉換或企業項目。