Introduction to Deep Learning Business Applications for Developers: From Conversational Bots in Customer Service to Medical Image Processing
暫譯: 深度學習商業應用開發者入門:從客服對話機器人到醫療影像處理

Armando Vieira

商品描述

Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. 

An Introduction to Deep Learning Business Applications for Developers covers some common DL algorithms such as content-based recommendation algorithms and natural language processing. You’ll explore examples, such as video prediction with fully convolutional neural networks (FCNN) and residual neural networks (ResNets). You will also see applications of DL for controlling robotics, exploring the DeepQ learning algorithm with Monte Carlo Tree search (used to beat humans in the game of Go), and modeling for financial risk assessment. There will also be mention of the powerful set of algorithms called Generative Adversarial Neural networks (GANs) that can be applied for image colorization, image completion, and style transfer.

After reading this book you will have an overview of the exciting field of deep neural networks and an understanding of most of the major applications of deep learning. The book contains some coding examples, tricks, and insights on how to train deep learning models using the Keras framework.

What You Will Learn

  • Find out about deep learning and why it is so powerful
  • Work with the major algorithms available to train deep learning models
  • See the major breakthroughs in terms of applications of deep learning  
  • Run simple examples with a selection of deep learning libraries 
  • Discover the areas of impact of deep learning in business

Who This Book Is For 
Data scientists, entrepreneurs, and business developers.


商品描述(中文翻譯)


從商業的角度探索深度學習的潛在應用、挑戰和機會,並提供技術範例。這些應用包括圖像識別、分割和標註、視頻處理和標註、語音識別、智能個人助理、自動翻譯和自駕車。




深度學習商業應用入門:為開發者而作涵蓋了一些常見的深度學習(DL)演算法,例如基於內容的推薦演算法和自然語言處理。您將探索一些範例,例如使用全卷積神經網絡(FCNN)和殘差神經網絡(ResNets)進行視頻預測。您還將看到深度學習在控制機器人方面的應用,探索使用蒙地卡羅樹搜索的DeepQ學習演算法(用於在圍棋遊戲中擊敗人類),以及金融風險評估的建模。此外,還會提到一組強大的演算法,稱為生成對抗神經網絡(GANs),可應用於圖像上色、圖像補全和風格轉換。



閱讀本書後,您將對深度神經網絡這一令人興奮的領域有一個概覽,並了解大多數深度學習的主要應用。本書包含一些編碼範例、技巧和如何使用Keras框架訓練深度學習模型的見解。



您將學到什麼


  • 了解深度學習及其強大的原因


  • 使用可用的主要演算法訓練深度學習模型


  • 了解深度學習應用方面的重大突破


  • 使用選定的深度學習庫運行簡單範例


  • 發現深度學習在商業中的影響領域



本書適合誰
數據科學家、企業家和商業開發者。